Overview

Dataset statistics

Number of variables366
Number of observations42833
Missing cells2186771
Missing cells (%)13.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory128.1 MiB
Average record size in memory3.1 KiB

Variable types

NUM328
CAT32
BOOL6

Warnings

EINGEFUEGT_AM has a high cardinality: 1608 distinct values High cardinality
AKT_DAT_KL has 6889 (16.1%) missing values Missing
ALTER_HH has 6889 (16.1%) missing values Missing
ALTER_KIND1 has 40820 (95.3%) missing values Missing
ALTER_KIND2 has 42071 (98.2%) missing values Missing
ALTER_KIND3 has 42632 (99.5%) missing values Missing
ALTER_KIND4 has 42794 (99.9%) missing values Missing
ALTERSKATEGORIE_FEIN has 8118 (19.0%) missing values Missing
ANZ_HAUSHALTE_AKTIV has 7627 (17.8%) missing values Missing
ANZ_HH_TITEL has 8146 (19.0%) missing values Missing
ANZ_KINDER has 6889 (16.1%) missing values Missing
ANZ_PERSONEN has 6889 (16.1%) missing values Missing
ANZ_STATISTISCHE_HAUSHALTE has 7627 (17.8%) missing values Missing
ANZ_TITEL has 6889 (16.1%) missing values Missing
ARBEIT has 7783 (18.2%) missing values Missing
BALLRAUM has 7641 (17.8%) missing values Missing
CAMEO_DEU_2015 has 7740 (18.1%) missing values Missing
CAMEO_DEUG_2015 has 7747 (18.1%) missing values Missing
CAMEO_INTL_2015 has 7747 (18.1%) missing values Missing
CJT_GESAMTTYP has 578 (1.3%) missing values Missing
CJT_KATALOGNUTZER has 578 (1.3%) missing values Missing
CJT_TYP_1 has 578 (1.3%) missing values Missing
CJT_TYP_2 has 578 (1.3%) missing values Missing
CJT_TYP_3 has 578 (1.3%) missing values Missing
CJT_TYP_4 has 578 (1.3%) missing values Missing
CJT_TYP_5 has 578 (1.3%) missing values Missing
CJT_TYP_6 has 578 (1.3%) missing values Missing
D19_BANKEN_ONLINE_QUOTE_12 has 7526 (17.6%) missing values Missing
D19_GESAMT_ONLINE_QUOTE_12 has 7526 (17.6%) missing values Missing
D19_KONSUMTYP has 7526 (17.6%) missing values Missing
D19_LETZTER_KAUF_BRANCHE has 7526 (17.6%) missing values Missing
D19_LOTTO has 7526 (17.6%) missing values Missing
D19_SOZIALES has 7526 (17.6%) missing values Missing
D19_TELKO_ONLINE_QUOTE_12 has 7526 (17.6%) missing values Missing
D19_VERSAND_ONLINE_QUOTE_12 has 7526 (17.6%) missing values Missing
D19_VERSI_ONLINE_QUOTE_12 has 7526 (17.6%) missing values Missing
DSL_FLAG has 7627 (17.8%) missing values Missing
EINGEFUEGT_AM has 7627 (17.8%) missing values Missing
EINGEZOGENAM_HH_JAHR has 6889 (16.1%) missing values Missing
EWDICHTE has 7641 (17.8%) missing values Missing
EXTSEL992 has 15809 (36.9%) missing values Missing
FIRMENDICHTE has 7627 (17.8%) missing values Missing
GEBAEUDETYP has 7627 (17.8%) missing values Missing
GEBAEUDETYP_RASTER has 7627 (17.8%) missing values Missing
GEMEINDETYP has 7784 (18.2%) missing values Missing
GFK_URLAUBERTYP has 578 (1.3%) missing values Missing
HH_DELTA_FLAG has 9619 (22.5%) missing values Missing
HH_EINKOMMEN_SCORE has 642 (1.5%) missing values Missing
INNENSTADT has 7641 (17.8%) missing values Missing
KBA05_ALTER1 has 8537 (19.9%) missing values Missing
KBA05_ALTER2 has 8537 (19.9%) missing values Missing
KBA05_ALTER3 has 8537 (19.9%) missing values Missing
KBA05_ALTER4 has 8537 (19.9%) missing values Missing
KBA05_ANHANG has 8537 (19.9%) missing values Missing
KBA05_ANTG1 has 8537 (19.9%) missing values Missing
KBA05_ANTG2 has 8537 (19.9%) missing values Missing
KBA05_ANTG3 has 8537 (19.9%) missing values Missing
KBA05_ANTG4 has 8537 (19.9%) missing values Missing
KBA05_AUTOQUOT has 8537 (19.9%) missing values Missing
KBA05_BAUMAX has 8537 (19.9%) missing values Missing
KBA05_CCM1 has 8537 (19.9%) missing values Missing
KBA05_CCM2 has 8537 (19.9%) missing values Missing
KBA05_CCM3 has 8537 (19.9%) missing values Missing
KBA05_CCM4 has 8537 (19.9%) missing values Missing
KBA05_DIESEL has 8537 (19.9%) missing values Missing
KBA05_FRAU has 8537 (19.9%) missing values Missing
KBA05_GBZ has 8537 (19.9%) missing values Missing
KBA05_HERST1 has 8537 (19.9%) missing values Missing
KBA05_HERST2 has 8537 (19.9%) missing values Missing
KBA05_HERST3 has 8537 (19.9%) missing values Missing
KBA05_HERST4 has 8537 (19.9%) missing values Missing
KBA05_HERST5 has 8537 (19.9%) missing values Missing
KBA05_HERSTTEMP has 7627 (17.8%) missing values Missing
KBA05_KRSAQUOT has 8537 (19.9%) missing values Missing
KBA05_KRSHERST1 has 8537 (19.9%) missing values Missing
KBA05_KRSHERST2 has 8537 (19.9%) missing values Missing
KBA05_KRSHERST3 has 8537 (19.9%) missing values Missing
KBA05_KRSKLEIN has 8537 (19.9%) missing values Missing
KBA05_KRSOBER has 8537 (19.9%) missing values Missing
KBA05_KRSVAN has 8537 (19.9%) missing values Missing
KBA05_KRSZUL has 8537 (19.9%) missing values Missing
KBA05_KW1 has 8537 (19.9%) missing values Missing
KBA05_KW2 has 8537 (19.9%) missing values Missing
KBA05_KW3 has 8537 (19.9%) missing values Missing
KBA05_MAXAH has 8537 (19.9%) missing values Missing
KBA05_MAXBJ has 8537 (19.9%) missing values Missing
KBA05_MAXHERST has 8537 (19.9%) missing values Missing
KBA05_MAXSEG has 8537 (19.9%) missing values Missing
KBA05_MAXVORB has 8537 (19.9%) missing values Missing
KBA05_MOD1 has 8537 (19.9%) missing values Missing
KBA05_MOD2 has 8537 (19.9%) missing values Missing
KBA05_MOD3 has 8537 (19.9%) missing values Missing
KBA05_MOD4 has 8537 (19.9%) missing values Missing
KBA05_MOD8 has 8537 (19.9%) missing values Missing
KBA05_MODTEMP has 7627 (17.8%) missing values Missing
KBA05_MOTOR has 8537 (19.9%) missing values Missing
KBA05_MOTRAD has 8537 (19.9%) missing values Missing
KBA05_SEG1 has 8537 (19.9%) missing values Missing
KBA05_SEG10 has 8537 (19.9%) missing values Missing
KBA05_SEG2 has 8537 (19.9%) missing values Missing
KBA05_SEG3 has 8537 (19.9%) missing values Missing
KBA05_SEG4 has 8537 (19.9%) missing values Missing
KBA05_SEG5 has 8537 (19.9%) missing values Missing
KBA05_SEG6 has 8537 (19.9%) missing values Missing
KBA05_SEG7 has 8537 (19.9%) missing values Missing
KBA05_SEG8 has 8537 (19.9%) missing values Missing
KBA05_SEG9 has 8537 (19.9%) missing values Missing
KBA05_VORB0 has 8537 (19.9%) missing values Missing
KBA05_VORB1 has 8537 (19.9%) missing values Missing
KBA05_VORB2 has 8537 (19.9%) missing values Missing
KBA05_ZUL1 has 8537 (19.9%) missing values Missing
KBA05_ZUL2 has 8537 (19.9%) missing values Missing
KBA05_ZUL3 has 8537 (19.9%) missing values Missing
KBA05_ZUL4 has 8537 (19.9%) missing values Missing
KBA13_ALTERHALTER_30 has 7841 (18.3%) missing values Missing
KBA13_ALTERHALTER_45 has 7841 (18.3%) missing values Missing
KBA13_ALTERHALTER_60 has 7841 (18.3%) missing values Missing
KBA13_ALTERHALTER_61 has 7841 (18.3%) missing values Missing
KBA13_ANTG1 has 7841 (18.3%) missing values Missing
KBA13_ANTG2 has 7841 (18.3%) missing values Missing
KBA13_ANTG3 has 7841 (18.3%) missing values Missing
KBA13_ANTG4 has 7841 (18.3%) missing values Missing
KBA13_ANZAHL_PKW has 7841 (18.3%) missing values Missing
KBA13_AUDI has 7841 (18.3%) missing values Missing
KBA13_AUTOQUOTE has 7841 (18.3%) missing values Missing
KBA13_BAUMAX has 7841 (18.3%) missing values Missing
KBA13_BJ_1999 has 7841 (18.3%) missing values Missing
KBA13_BJ_2000 has 7841 (18.3%) missing values Missing
KBA13_BJ_2004 has 7841 (18.3%) missing values Missing
KBA13_BJ_2006 has 7841 (18.3%) missing values Missing
KBA13_BJ_2008 has 7841 (18.3%) missing values Missing
KBA13_BJ_2009 has 7841 (18.3%) missing values Missing
KBA13_BMW has 7841 (18.3%) missing values Missing
KBA13_CCM_0_1400 has 7841 (18.3%) missing values Missing
KBA13_CCM_1000 has 7841 (18.3%) missing values Missing
KBA13_CCM_1200 has 7841 (18.3%) missing values Missing
KBA13_CCM_1400 has 7841 (18.3%) missing values Missing
KBA13_CCM_1401_2500 has 7841 (18.3%) missing values Missing
KBA13_CCM_1500 has 7841 (18.3%) missing values Missing
KBA13_CCM_1600 has 7841 (18.3%) missing values Missing
KBA13_CCM_1800 has 7841 (18.3%) missing values Missing
KBA13_CCM_2000 has 7841 (18.3%) missing values Missing
KBA13_CCM_2500 has 7841 (18.3%) missing values Missing
KBA13_CCM_2501 has 7841 (18.3%) missing values Missing
KBA13_CCM_3000 has 7841 (18.3%) missing values Missing
KBA13_CCM_3001 has 7841 (18.3%) missing values Missing
KBA13_FAB_ASIEN has 7841 (18.3%) missing values Missing
KBA13_FAB_SONSTIGE has 7841 (18.3%) missing values Missing
KBA13_FIAT has 7841 (18.3%) missing values Missing
KBA13_FORD has 7841 (18.3%) missing values Missing
KBA13_GBZ has 7841 (18.3%) missing values Missing
KBA13_HALTER_20 has 7841 (18.3%) missing values Missing
KBA13_HALTER_25 has 7841 (18.3%) missing values Missing
KBA13_HALTER_30 has 7841 (18.3%) missing values Missing
KBA13_HALTER_35 has 7841 (18.3%) missing values Missing
KBA13_HALTER_40 has 7841 (18.3%) missing values Missing
KBA13_HALTER_45 has 7841 (18.3%) missing values Missing
KBA13_HALTER_50 has 7841 (18.3%) missing values Missing
KBA13_HALTER_55 has 7841 (18.3%) missing values Missing
KBA13_HALTER_60 has 7841 (18.3%) missing values Missing
KBA13_HALTER_65 has 7841 (18.3%) missing values Missing
KBA13_HALTER_66 has 7841 (18.3%) missing values Missing
KBA13_HERST_ASIEN has 7841 (18.3%) missing values Missing
KBA13_HERST_AUDI_VW has 7841 (18.3%) missing values Missing
KBA13_HERST_BMW_BENZ has 7841 (18.3%) missing values Missing
KBA13_HERST_EUROPA has 7841 (18.3%) missing values Missing
KBA13_HERST_FORD_OPEL has 7841 (18.3%) missing values Missing
KBA13_HERST_SONST has 7841 (18.3%) missing values Missing
KBA13_HHZ has 7841 (18.3%) missing values Missing
KBA13_KMH_0_140 has 7841 (18.3%) missing values Missing
KBA13_KMH_110 has 7841 (18.3%) missing values Missing
KBA13_KMH_140 has 7841 (18.3%) missing values Missing
KBA13_KMH_140_210 has 7841 (18.3%) missing values Missing
KBA13_KMH_180 has 7841 (18.3%) missing values Missing
KBA13_KMH_210 has 7841 (18.3%) missing values Missing
KBA13_KMH_211 has 7841 (18.3%) missing values Missing
KBA13_KMH_250 has 7841 (18.3%) missing values Missing
KBA13_KMH_251 has 7841 (18.3%) missing values Missing
KBA13_KRSAQUOT has 7841 (18.3%) missing values Missing
KBA13_KRSHERST_AUDI_VW has 7841 (18.3%) missing values Missing
KBA13_KRSHERST_BMW_BENZ has 7841 (18.3%) missing values Missing
KBA13_KRSHERST_FORD_OPEL has 7841 (18.3%) missing values Missing
KBA13_KRSSEG_KLEIN has 7841 (18.3%) missing values Missing
KBA13_KRSSEG_OBER has 7841 (18.3%) missing values Missing
KBA13_KRSSEG_VAN has 7841 (18.3%) missing values Missing
KBA13_KRSZUL_NEU has 7841 (18.3%) missing values Missing
KBA13_KW_0_60 has 7841 (18.3%) missing values Missing
KBA13_KW_110 has 7841 (18.3%) missing values Missing
KBA13_KW_120 has 7841 (18.3%) missing values Missing
KBA13_KW_121 has 7841 (18.3%) missing values Missing
KBA13_KW_30 has 7841 (18.3%) missing values Missing
KBA13_KW_40 has 7841 (18.3%) missing values Missing
KBA13_KW_50 has 7841 (18.3%) missing values Missing
KBA13_KW_60 has 7841 (18.3%) missing values Missing
KBA13_KW_61_120 has 7841 (18.3%) missing values Missing
KBA13_KW_70 has 7841 (18.3%) missing values Missing
KBA13_KW_80 has 7841 (18.3%) missing values Missing
KBA13_KW_90 has 7841 (18.3%) missing values Missing
KBA13_MAZDA has 7841 (18.3%) missing values Missing
KBA13_MERCEDES has 7841 (18.3%) missing values Missing
KBA13_MOTOR has 7841 (18.3%) missing values Missing
KBA13_NISSAN has 7841 (18.3%) missing values Missing
KBA13_OPEL has 7841 (18.3%) missing values Missing
KBA13_PEUGEOT has 7841 (18.3%) missing values Missing
KBA13_RENAULT has 7841 (18.3%) missing values Missing
KBA13_SEG_GELAENDEWAGEN has 7841 (18.3%) missing values Missing
KBA13_SEG_GROSSRAUMVANS has 7841 (18.3%) missing values Missing
KBA13_SEG_KLEINST has 7841 (18.3%) missing values Missing
KBA13_SEG_KLEINWAGEN has 7841 (18.3%) missing values Missing
KBA13_SEG_KOMPAKTKLASSE has 7841 (18.3%) missing values Missing
KBA13_SEG_MINIVANS has 7841 (18.3%) missing values Missing
KBA13_SEG_MINIWAGEN has 7841 (18.3%) missing values Missing
KBA13_SEG_MITTELKLASSE has 7841 (18.3%) missing values Missing
KBA13_SEG_OBEREMITTELKLASSE has 7841 (18.3%) missing values Missing
KBA13_SEG_OBERKLASSE has 7841 (18.3%) missing values Missing
KBA13_SEG_SONSTIGE has 7841 (18.3%) missing values Missing
KBA13_SEG_SPORTWAGEN has 7841 (18.3%) missing values Missing
KBA13_SEG_UTILITIES has 7841 (18.3%) missing values Missing
KBA13_SEG_VAN has 7841 (18.3%) missing values Missing
KBA13_SEG_WOHNMOBILE has 7841 (18.3%) missing values Missing
KBA13_SITZE_4 has 7841 (18.3%) missing values Missing
KBA13_SITZE_5 has 7841 (18.3%) missing values Missing
KBA13_SITZE_6 has 7841 (18.3%) missing values Missing
KBA13_TOYOTA has 7841 (18.3%) missing values Missing
KBA13_VORB_0 has 7841 (18.3%) missing values Missing
KBA13_VORB_1 has 7841 (18.3%) missing values Missing
KBA13_VORB_1_2 has 7841 (18.3%) missing values Missing
KBA13_VORB_2 has 7841 (18.3%) missing values Missing
KBA13_VORB_3 has 7841 (18.3%) missing values Missing
KBA13_VW has 7841 (18.3%) missing values Missing
KK_KUNDENTYP has 25035 (58.4%) missing values Missing
KKK has 8303 (19.4%) missing values Missing
KONSUMNAEHE has 6926 (16.2%) missing values Missing
KONSUMZELLE has 7627 (17.8%) missing values Missing
LP_FAMILIE_FEIN has 578 (1.3%) missing values Missing
LP_FAMILIE_GROB has 578 (1.3%) missing values Missing
LP_LEBENSPHASE_FEIN has 578 (1.3%) missing values Missing
LP_LEBENSPHASE_GROB has 578 (1.3%) missing values Missing
LP_STATUS_FEIN has 578 (1.3%) missing values Missing
LP_STATUS_GROB has 578 (1.3%) missing values Missing
MIN_GEBAEUDEJAHR has 7627 (17.8%) missing values Missing
MOBI_RASTER has 7627 (17.8%) missing values Missing
MOBI_REGIO has 8537 (19.9%) missing values Missing
ONLINE_AFFINITAET has 578 (1.3%) missing values Missing
ORTSGR_KLS9 has 7783 (18.2%) missing values Missing
OST_WEST_KZ has 7627 (17.8%) missing values Missing
PLZ8_ANTG1 has 8044 (18.8%) missing values Missing
PLZ8_ANTG2 has 8044 (18.8%) missing values Missing
PLZ8_ANTG3 has 8044 (18.8%) missing values Missing
PLZ8_ANTG4 has 8044 (18.8%) missing values Missing
PLZ8_BAUMAX has 8044 (18.8%) missing values Missing
PLZ8_GBZ has 8044 (18.8%) missing values Missing
PLZ8_HHZ has 8044 (18.8%) missing values Missing
REGIOTYP has 8303 (19.4%) missing values Missing
RELAT_AB has 7783 (18.2%) missing values Missing
RETOURTYP_BK_S has 578 (1.3%) missing values Missing
RT_KEIN_ANREIZ has 578 (1.3%) missing values Missing
RT_SCHNAEPPCHEN has 578 (1.3%) missing values Missing
RT_UEBERGROESSE has 6217 (14.5%) missing values Missing
SOHO_KZ has 6889 (16.1%) missing values Missing
STRUKTURTYP has 7784 (18.2%) missing values Missing
TITEL_KZ has 6889 (16.1%) missing values Missing
UMFELD_ALT has 7763 (18.1%) missing values Missing
UMFELD_JUNG has 7763 (18.1%) missing values Missing
UNGLEICHENN_FLAG has 6889 (16.1%) missing values Missing
VERDICHTUNGSRAUM has 7784 (18.2%) missing values Missing
VHA has 6889 (16.1%) missing values Missing
VHN has 8303 (19.4%) missing values Missing
VK_DHT4A has 7175 (16.8%) missing values Missing
VK_DISTANZ has 7175 (16.8%) missing values Missing
VK_ZG11 has 7175 (16.8%) missing values Missing
W_KEIT_KIND_HH has 9619 (22.5%) missing values Missing
WOHNDAUER_2008 has 6889 (16.1%) missing values Missing
WOHNLAGE has 7627 (17.8%) missing values Missing
ANZ_HH_TITEL is highly skewed (γ1 = 21.40253768) Skewed
D19_VERSI_ONLINE_DATUM is highly skewed (γ1 = -20.76506053) Skewed
TITEL_KZ is highly skewed (γ1 = 23.54853598) Skewed
LNR has unique values Unique
AGER_TYP has 928 (2.2%) zeros Zeros
ALTER_HH has 6342 (14.8%) zeros Zeros
ALTERSKATEGORIE_FEIN has 3661 (8.5%) zeros Zeros
ANZ_HAUSHALTE_AKTIV has 580 (1.4%) zeros Zeros
ANZ_HH_TITEL has 33491 (78.2%) zeros Zeros
ANZ_KINDER has 33749 (78.8%) zeros Zeros
ANZ_PERSONEN has 2730 (6.4%) zeros Zeros
D19_BANKEN_ANZ_12 has 40055 (93.5%) zeros Zeros
D19_BANKEN_ANZ_24 has 38560 (90.0%) zeros Zeros
D19_BANKEN_DIREKT has 36690 (85.7%) zeros Zeros
D19_BANKEN_GROSS has 38753 (90.5%) zeros Zeros
D19_BANKEN_LOKAL has 41978 (98.0%) zeros Zeros
D19_BANKEN_ONLINE_QUOTE_12 has 33740 (78.8%) zeros Zeros
D19_BANKEN_REST has 39736 (92.8%) zeros Zeros
D19_BEKLEIDUNG_GEH has 35744 (83.4%) zeros Zeros
D19_BEKLEIDUNG_REST has 29888 (69.8%) zeros Zeros
D19_BILDUNG has 34643 (80.9%) zeros Zeros
D19_BIO_OEKO has 38272 (89.4%) zeros Zeros
D19_BUCH_CD has 22306 (52.1%) zeros Zeros
D19_DIGIT_SERV has 41122 (96.0%) zeros Zeros
D19_DROGERIEARTIKEL has 36583 (85.4%) zeros Zeros
D19_ENERGIE has 39059 (91.2%) zeros Zeros
D19_FREIZEIT has 37632 (87.9%) zeros Zeros
D19_GARTEN has 39649 (92.6%) zeros Zeros
D19_GESAMT_ANZ_12 has 25068 (58.5%) zeros Zeros
D19_GESAMT_ANZ_24 has 20500 (47.9%) zeros Zeros
D19_GESAMT_ONLINE_QUOTE_12 has 23181 (54.1%) zeros Zeros
D19_HANDWERK has 30723 (71.7%) zeros Zeros
D19_HAUS_DEKO has 28399 (66.3%) zeros Zeros
D19_KINDERARTIKEL has 33680 (78.6%) zeros Zeros
D19_KOSMETIK has 28543 (66.6%) zeros Zeros
D19_LEBENSMITTEL has 37291 (87.1%) zeros Zeros
D19_LOTTO has 20136 (47.0%) zeros Zeros
D19_NAHRUNGSERGAENZUNG has 38321 (89.5%) zeros Zeros
D19_RATGEBER has 35102 (82.0%) zeros Zeros
D19_REISEN has 27986 (65.3%) zeros Zeros
D19_SAMMELARTIKEL has 31815 (74.3%) zeros Zeros
D19_SCHUHE has 37362 (87.2%) zeros Zeros
D19_SONSTIGE has 15027 (35.1%) zeros Zeros
D19_SOZIALES has 9585 (22.4%) zeros Zeros
D19_TECHNIK has 25431 (59.4%) zeros Zeros
D19_TELKO_ANZ_12 has 41050 (95.8%) zeros Zeros
D19_TELKO_ANZ_24 has 39657 (92.6%) zeros Zeros
D19_TELKO_MOBILE has 35991 (84.0%) zeros Zeros
D19_TELKO_REST has 37808 (88.3%) zeros Zeros
D19_TIERARTIKEL has 40738 (95.1%) zeros Zeros
D19_VERSAND_ANZ_12 has 27471 (64.1%) zeros Zeros
D19_VERSAND_ANZ_24 has 23150 (54.0%) zeros Zeros
D19_VERSAND_ONLINE_QUOTE_12 has 24464 (57.1%) zeros Zeros
D19_VERSAND_REST has 36177 (84.5%) zeros Zeros
D19_VERSI_ANZ_12 has 39452 (92.1%) zeros Zeros
D19_VERSI_ANZ_24 has 37442 (87.4%) zeros Zeros
D19_VERSICHERUNGEN has 31891 (74.5%) zeros Zeros
D19_VOLLSORTIMENT has 20117 (47.0%) zeros Zeros
D19_WEIN_FEINKOST has 36598 (85.4%) zeros Zeros
GEBURTSJAHR has 17583 (41.1%) zeros Zeros
KBA05_ALTER1 has 5183 (12.1%) zeros Zeros
KBA05_ALTER4 has 819 (1.9%) zeros Zeros
KBA05_ANHANG has 9844 (23.0%) zeros Zeros
KBA05_ANTG1 has 9113 (21.3%) zeros Zeros
KBA05_ANTG2 has 12881 (30.1%) zeros Zeros
KBA05_BAUMAX has 14287 (33.4%) zeros Zeros
KBA05_CCM4 has 11018 (25.7%) zeros Zeros
KBA05_DIESEL has 2427 (5.7%) zeros Zeros
KBA05_HERST1 has 2594 (6.1%) zeros Zeros
KBA05_HERST3 has 519 (1.2%) zeros Zeros
KBA05_HERST4 has 1045 (2.4%) zeros Zeros
KBA05_HERST5 has 1654 (3.9%) zeros Zeros
KBA05_KW3 has 7876 (18.4%) zeros Zeros
KBA05_MOD1 has 11659 (27.2%) zeros Zeros
KBA05_MOD4 has 1719 (4.0%) zeros Zeros
KBA05_MOD8 has 8550 (20.0%) zeros Zeros
KBA05_MOTRAD has 8115 (18.9%) zeros Zeros
KBA05_SEG1 has 10315 (24.1%) zeros Zeros
KBA05_SEG10 has 3992 (9.3%) zeros Zeros
KBA05_SEG5 has 7113 (16.6%) zeros Zeros
KBA05_SEG7 has 15140 (35.3%) zeros Zeros
KBA05_SEG8 has 17271 (40.3%) zeros Zeros
KBA05_SEG9 has 10277 (24.0%) zeros Zeros
KBA05_VORB2 has 2710 (6.3%) zeros Zeros
KBA05_ZUL3 has 1971 (4.6%) zeros Zeros
KBA05_ZUL4 has 3327 (7.8%) zeros Zeros
KBA13_ANTG2 has 501 (1.2%) zeros Zeros
KBA13_BJ_2008 has 5495 (12.8%) zeros Zeros
KBA13_BJ_2009 has 4165 (9.7%) zeros Zeros
KBA13_CCM_0_1400 has 6437 (15.0%) zeros Zeros
KBA13_CCM_1000 has 4466 (10.4%) zeros Zeros
KBA13_CCM_1200 has 6755 (15.8%) zeros Zeros
KBA13_CCM_1800 has 5935 (13.9%) zeros Zeros
KBA13_CCM_2500 has 4158 (9.7%) zeros Zeros
KBA13_CCM_2501 has 3962 (9.2%) zeros Zeros
KBA13_CCM_3000 has 2530 (5.9%) zeros Zeros
KBA13_KMH_0_140 has 4639 (10.8%) zeros Zeros
KBA13_KMH_211 has 5878 (13.7%) zeros Zeros
KBA13_KMH_250 has 5951 (13.9%) zeros Zeros
KBA13_KW_110 has 5392 (12.6%) zeros Zeros
KBA13_KW_120 has 4056 (9.5%) zeros Zeros
KBA13_KW_121 has 4109 (9.6%) zeros Zeros
KBA13_KW_40 has 4472 (10.4%) zeros Zeros
KBA13_KW_50 has 6557 (15.3%) zeros Zeros
KBA13_KW_60 has 6058 (14.1%) zeros Zeros
KBA13_KW_70 has 6512 (15.2%) zeros Zeros
KBA13_KW_80 has 5694 (13.3%) zeros Zeros
KBA13_KW_90 has 6039 (14.1%) zeros Zeros
KBA13_SEG_OBERKLASSE has 3921 (9.2%) zeros Zeros
KBA13_SEG_SPORTWAGEN has 3574 (8.3%) zeros Zeros
KBA13_SEG_WOHNMOBILE has 3876 (9.0%) zeros Zeros
KBA13_VORB_3 has 7322 (17.1%) zeros Zeros
KKK has 1539 (3.6%) zeros Zeros
LP_FAMILIE_FEIN has 8073 (18.8%) zeros Zeros
LP_FAMILIE_GROB has 8073 (18.8%) zeros Zeros
LP_LEBENSPHASE_FEIN has 8156 (19.0%) zeros Zeros
LP_LEBENSPHASE_GROB has 8135 (19.0%) zeros Zeros
ONLINE_AFFINITAET has 2105 (4.9%) zeros Zeros
PRAEGENDE_JUGENDJAHRE has 7365 (17.2%) zeros Zeros
REGIOTYP has 1539 (3.6%) zeros Zeros
SHOPPER_TYP has 6092 (14.2%) zeros Zeros
TITEL_KZ has 35698 (83.3%) zeros Zeros
VERDICHTUNGSRAUM has 17366 (40.5%) zeros Zeros
VHA has 16026 (37.4%) zeros Zeros
VHN has 1539 (3.6%) zeros Zeros
W_KEIT_KIND_HH has 711 (1.7%) zeros Zeros

Reproduction

Analysis started2020-11-30 14:57:44.557680
Analysis finished2020-11-30 14:57:50.972924
Duration6.42 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

LNR
Real number (ℝ≥0)

UNIQUE

Distinct42833
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42993.16562
Minimum2
Maximum85794
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:51.075825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4372.6
Q121650
median43054
Q364352
95-th percentile81641.8
Maximum85794
Range85792
Interquartile range (IQR)42702

Descriptive statistics

Standard deviation24755.59973
Coefficient of variation (CV)0.5758031392
Kurtosis-1.196611944
Mean42993.16562
Median Absolute Deviation (MAD)21349
Skewness-0.002145564174
Sum1841526263
Variance612839717.9
MonotocityNot monotonic
2020-11-30T23:57:51.203761image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
675831< 0.1%
 
853471< 0.1%
 
239051< 0.1%
 
218561< 0.1%
 
464281< 0.1%
 
361871< 0.1%
 
402811< 0.1%
 
382321< 0.1%
 
587101< 0.1%
 
505141< 0.1%
 
771351< 0.1%
 
95501< 0.1%
 
812291< 0.1%
 
791801< 0.1%
 
689391< 0.1%
 
13541< 0.1%
 
74971< 0.1%
 
709841< 0.1%
 
279751< 0.1%
 
177621< 0.1%
 
747611< 0.1%
 
300201< 0.1%
 
75291< 0.1%
 
444151< 0.1%
 
423661< 0.1%
 
Other values (42808)4280899.9%
 
ValueCountFrequency (%) 
21< 0.1%
 
31< 0.1%
 
41< 0.1%
 
61< 0.1%
 
71< 0.1%
 
81< 0.1%
 
151< 0.1%
 
161< 0.1%
 
171< 0.1%
 
181< 0.1%
 
ValueCountFrequency (%) 
857941< 0.1%
 
857931< 0.1%
 
857911< 0.1%
 
857901< 0.1%
 
857891< 0.1%
 
857871< 0.1%
 
857851< 0.1%
 
857841< 0.1%
 
857831< 0.1%
 
857811< 0.1%
 

AGER_TYP
Real number (ℝ)

ZEROS

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.537436089
Minimum-1
Maximum3
Zeros928
Zeros (%)2.2%
Memory size334.8 KiB
2020-11-30T23:57:51.306828image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-1
median1
Q32
95-th percentile3
Maximum3
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.414776577
Coefficient of variation (CV)2.632455479
Kurtosis-1.562790354
Mean0.537436089
Median Absolute Deviation (MAD)1
Skewness0.08269847981
Sum23020
Variance2.001592763
MonotocityNot monotonic
2020-11-30T23:57:51.395338image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
-11799742.0%
 
21223728.6%
 
1923521.6%
 
324365.7%
 
09282.2%
 
ValueCountFrequency (%) 
-11799742.0%
 
09282.2%
 
1923521.6%
 
21223728.6%
 
324365.7%
 
ValueCountFrequency (%) 
324365.7%
 
21223728.6%
 
1923521.6%
 
09282.2%
 
-11799742.0%
 

AKT_DAT_KL
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean1.518890496
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:51.489574image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile6
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.737440961
Coefficient of variation (CV)1.14388823
Kurtosis11.2342742
Mean1.518890496
Median Absolute Deviation (MAD)0
Skewness3.515750111
Sum54595
Variance3.018701092
MonotocityNot monotonic
2020-11-30T23:57:51.580958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
13200774.7%
 
912182.8%
 
27991.9%
 
54641.1%
 
33850.9%
 
43010.7%
 
62840.7%
 
72430.6%
 
82430.6%
 
(Missing)688916.1%
 
ValueCountFrequency (%) 
13200774.7%
 
27991.9%
 
33850.9%
 
43010.7%
 
54641.1%
 
62840.7%
 
72430.6%
 
82430.6%
 
912182.8%
 
ValueCountFrequency (%) 
912182.8%
 
82430.6%
 
72430.6%
 
62840.7%
 
54641.1%
 
43010.7%
 
33850.9%
 
27991.9%
 
13200774.7%
 

ALTER_HH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct21
Distinct (%)0.1%
Missing6889
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean10.23951146
Minimum0
Maximum21
Zeros6342
Zeros (%)14.8%
Memory size334.8 KiB
2020-11-30T23:57:51.682439image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median10
Q315
95-th percentile20
Maximum21
Range21
Interquartile range (IQR)7

Descriptive statistics

Standard deviation6.109679825
Coefficient of variation (CV)0.5966768872
Kurtosis-0.6603612325
Mean10.23951146
Median Absolute Deviation (MAD)3
Skewness-0.2180068208
Sum368049
Variance37.32818757
MonotocityNot monotonic
2020-11-30T23:57:51.770973image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
0634214.8%
 
939949.3%
 
1036328.5%
 
825986.1%
 
1123625.5%
 
1221955.1%
 
1317074.0%
 
716653.9%
 
1515253.6%
 
2114283.3%
 
1413953.3%
 
1613663.2%
 
1912482.9%
 
1712322.9%
 
2011962.8%
 
1811542.7%
 
67561.8%
 
51080.3%
 
4360.1%
 
34< 0.1%
 
21< 0.1%
 
(Missing)688916.1%
 
ValueCountFrequency (%) 
0634214.8%
 
21< 0.1%
 
34< 0.1%
 
4360.1%
 
51080.3%
 
67561.8%
 
716653.9%
 
825986.1%
 
939949.3%
 
1036328.5%
 
ValueCountFrequency (%) 
2114283.3%
 
2011962.8%
 
1912482.9%
 
1811542.7%
 
1712322.9%
 
1613663.2%
 
1515253.6%
 
1413953.3%
 
1317074.0%
 
1221955.1%
 

ALTER_KIND1
Real number (ℝ≥0)

MISSING

Distinct17
Distinct (%)0.8%
Missing40820
Missing (%)95.3%
Infinite0
Infinite (%)0.0%
Mean12.53402881
Minimum2
Maximum18
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:51.861248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q19
median13
Q316
95-th percentile18
Maximum18
Range16
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.996079032
Coefficient of variation (CV)0.3188184016
Kurtosis-0.9341699166
Mean12.53402881
Median Absolute Deviation (MAD)3
Skewness-0.3509756
Sum25231
Variance15.96864763
MonotocityNot monotonic
2020-11-30T23:57:51.946346image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%) 
182210.5%
 
172060.5%
 
151780.4%
 
141770.4%
 
161650.4%
 
131470.3%
 
91350.3%
 
101310.3%
 
81300.3%
 
111290.3%
 
121210.3%
 
71160.3%
 
6870.2%
 
5310.1%
 
317< 0.1%
 
416< 0.1%
 
26< 0.1%
 
(Missing)4082095.3%
 
ValueCountFrequency (%) 
26< 0.1%
 
317< 0.1%
 
416< 0.1%
 
5310.1%
 
6870.2%
 
71160.3%
 
81300.3%
 
91350.3%
 
101310.3%
 
111290.3%
 
ValueCountFrequency (%) 
182210.5%
 
172060.5%
 
161650.4%
 
151780.4%
 
141770.4%
 
131470.3%
 
121210.3%
 
111290.3%
 
101310.3%
 
91350.3%
 

ALTER_KIND2
Real number (ℝ≥0)

MISSING

Distinct15
Distinct (%)2.0%
Missing42071
Missing (%)98.2%
Infinite0
Infinite (%)0.0%
Mean13.94225722
Minimum4
Maximum18
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:52.038656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile8
Q112
median14
Q317
95-th percentile18
Maximum18
Range14
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.142155265
Coefficient of variation (CV)0.2253691935
Kurtosis-0.5186748724
Mean13.94225722
Median Absolute Deviation (MAD)2.5
Skewness-0.5438733524
Sum10624
Variance9.873139708
MonotocityNot monotonic
2020-11-30T23:57:52.125949image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
181090.3%
 
17970.2%
 
15870.2%
 
14840.2%
 
16760.2%
 
13700.2%
 
12640.1%
 
11510.1%
 
10430.1%
 
9330.1%
 
8290.1%
 
68< 0.1%
 
78< 0.1%
 
52< 0.1%
 
41< 0.1%
 
(Missing)4207198.2%
 
ValueCountFrequency (%) 
41< 0.1%
 
52< 0.1%
 
68< 0.1%
 
78< 0.1%
 
8290.1%
 
9330.1%
 
10430.1%
 
11510.1%
 
12640.1%
 
13700.2%
 
ValueCountFrequency (%) 
181090.3%
 
17970.2%
 
16760.2%
 
15870.2%
 
14840.2%
 
13700.2%
 
12640.1%
 
11510.1%
 
10430.1%
 
9330.1%
 

ALTER_KIND3
Real number (ℝ≥0)

MISSING

Distinct13
Distinct (%)6.5%
Missing42632
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean14.44278607
Minimum6
Maximum18
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:52.212594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile9
Q113
median15
Q317
95-th percentile18
Maximum18
Range12
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.787106062
Coefficient of variation (CV)0.1929756522
Kurtosis-0.07347284447
Mean14.44278607
Median Absolute Deviation (MAD)2
Skewness-0.699840764
Sum2903
Variance7.767960199
MonotocityNot monotonic
2020-11-30T23:57:52.315799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
17300.1%
 
18280.1%
 
15250.1%
 
14250.1%
 
16250.1%
 
13230.1%
 
1215< 0.1%
 
119< 0.1%
 
108< 0.1%
 
97< 0.1%
 
73< 0.1%
 
82< 0.1%
 
61< 0.1%
 
(Missing)4263299.5%
 
ValueCountFrequency (%) 
61< 0.1%
 
73< 0.1%
 
82< 0.1%
 
97< 0.1%
 
108< 0.1%
 
119< 0.1%
 
1215< 0.1%
 
13230.1%
 
14250.1%
 
15250.1%
 
ValueCountFrequency (%) 
18280.1%
 
17300.1%
 
16250.1%
 
15250.1%
 
14250.1%
 
13230.1%
 
1215< 0.1%
 
119< 0.1%
 
108< 0.1%
 
97< 0.1%
 

ALTER_KIND4
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)25.6%
Missing42794
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean14.41025641
Minimum9
Maximum18
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:52.409945image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile10.9
Q113
median14
Q316
95-th percentile18
Maximum18
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.279403762
Coefficient of variation (CV)0.1581792646
Kurtosis-0.5492586964
Mean14.41025641
Median Absolute Deviation (MAD)2
Skewness-0.2569132311
Sum562
Variance5.195681511
MonotocityNot monotonic
2020-11-30T23:57:52.492032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
137< 0.1%
 
176< 0.1%
 
155< 0.1%
 
145< 0.1%
 
125< 0.1%
 
165< 0.1%
 
183< 0.1%
 
111< 0.1%
 
91< 0.1%
 
101< 0.1%
 
(Missing)4279499.9%
 
ValueCountFrequency (%) 
91< 0.1%
 
101< 0.1%
 
111< 0.1%
 
125< 0.1%
 
137< 0.1%
 
145< 0.1%
 
155< 0.1%
 
165< 0.1%
 
176< 0.1%
 
183< 0.1%
 
ValueCountFrequency (%) 
183< 0.1%
 
176< 0.1%
 
165< 0.1%
 
155< 0.1%
 
145< 0.1%
 
137< 0.1%
 
125< 0.1%
 
111< 0.1%
 
101< 0.1%
 
91< 0.1%
 

ALTERSKATEGORIE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct25
Distinct (%)0.1%
Missing8118
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean9.822583897
Minimum0
Maximum25
Zeros3661
Zeros (%)8.5%
Memory size334.8 KiB
2020-11-30T23:57:52.583543image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q18
median10
Q313
95-th percentile16
Maximum25
Range25
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.410937105
Coefficient of variation (CV)0.4490607717
Kurtosis0.6380988428
Mean9.822583897
Median Absolute Deviation (MAD)2
Skewness-0.6264084525
Sum340991
Variance19.45636614
MonotocityNot monotonic
2020-11-30T23:57:52.683655image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%) 
9503511.8%
 
10456710.7%
 
036618.5%
 
832867.7%
 
1231437.3%
 
1130917.2%
 
1327266.4%
 
1421775.1%
 
719744.6%
 
1516173.8%
 
169172.1%
 
68472.0%
 
175701.3%
 
183750.9%
 
192830.7%
 
201560.4%
 
51280.3%
 
21710.2%
 
4390.1%
 
2517< 0.1%
 
2415< 0.1%
 
228< 0.1%
 
37< 0.1%
 
23< 0.1%
 
232< 0.1%
 
(Missing)811819.0%
 
ValueCountFrequency (%) 
036618.5%
 
23< 0.1%
 
37< 0.1%
 
4390.1%
 
51280.3%
 
68472.0%
 
719744.6%
 
832867.7%
 
9503511.8%
 
10456710.7%
 
ValueCountFrequency (%) 
2517< 0.1%
 
2415< 0.1%
 
232< 0.1%
 
228< 0.1%
 
21710.2%
 
201560.4%
 
192830.7%
 
183750.9%
 
175701.3%
 
169172.1%
 

ANZ_HAUSHALTE_AKTIV
Real number (ℝ≥0)

MISSING
ZEROS

Distinct178
Distinct (%)0.5%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean6.749985798
Minimum0
Maximum379
Zeros580
Zeros (%)1.4%
Memory size334.8 KiB
2020-11-30T23:57:52.796327image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q37
95-th percentile26
Maximum379
Range379
Interquartile range (IQR)6

Descriptive statistics

Standard deviation14.83977904
Coefficient of variation (CV)2.19849041
Kurtosis103.1975547
Mean6.749985798
Median Absolute Deviation (MAD)1
Skewness7.967103961
Sum237640
Variance220.219042
MonotocityNot monotonic
2020-11-30T23:57:52.916800image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
11372332.0%
 
2552412.9%
 
321094.9%
 
414133.3%
 
511952.8%
 
611922.8%
 
711212.6%
 
810862.5%
 
99182.1%
 
107491.7%
 
116391.5%
 
05801.4%
 
125551.3%
 
134481.0%
 
143850.9%
 
153020.7%
 
162340.5%
 
172140.5%
 
191780.4%
 
181690.4%
 
201600.4%
 
221230.3%
 
211210.3%
 
231040.2%
 
25940.2%
 
Other values (153)18704.4%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
05801.4%
 
11372332.0%
 
2552412.9%
 
321094.9%
 
414133.3%
 
511952.8%
 
611922.8%
 
711212.6%
 
810862.5%
 
99182.1%
 
ValueCountFrequency (%) 
3791< 0.1%
 
3661< 0.1%
 
3441< 0.1%
 
3311< 0.1%
 
2771< 0.1%
 
2671< 0.1%
 
2652< 0.1%
 
2591< 0.1%
 
2543< 0.1%
 
2532< 0.1%
 

ANZ_HH_TITEL
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct15
Distinct (%)< 0.1%
Missing8146
Missing (%)19.0%
Infinite0
Infinite (%)0.0%
Mean0.04566552311
Minimum0
Maximum20
Zeros33491
Zeros (%)78.2%
Memory size334.8 KiB
2020-11-30T23:57:53.026415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum20
Range20
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3394044006
Coefficient of variation (CV)7.43239927
Kurtosis820.2034387
Mean0.04566552311
Median Absolute Deviation (MAD)0
Skewness21.40253768
Sum1584
Variance0.1151953472
MonotocityNot monotonic
2020-11-30T23:57:53.120190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%) 
03349178.2%
 
110322.4%
 
2980.2%
 
3240.1%
 
412< 0.1%
 
68< 0.1%
 
77< 0.1%
 
56< 0.1%
 
102< 0.1%
 
112< 0.1%
 
201< 0.1%
 
121< 0.1%
 
91< 0.1%
 
181< 0.1%
 
81< 0.1%
 
(Missing)814619.0%
 
ValueCountFrequency (%) 
03349178.2%
 
110322.4%
 
2980.2%
 
3240.1%
 
412< 0.1%
 
56< 0.1%
 
68< 0.1%
 
77< 0.1%
 
81< 0.1%
 
91< 0.1%
 
ValueCountFrequency (%) 
201< 0.1%
 
181< 0.1%
 
121< 0.1%
 
112< 0.1%
 
102< 0.1%
 
91< 0.1%
 
81< 0.1%
 
77< 0.1%
 
68< 0.1%
 
56< 0.1%
 

ANZ_KINDER
Real number (ℝ≥0)

MISSING
ZEROS

Distinct8
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean0.09075228133
Minimum0
Maximum7
Zeros33749
Zeros (%)78.8%
Memory size334.8 KiB
2020-11-30T23:57:53.215355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4001073103
Coefficient of variation (CV)4.408785151
Kurtosis35.33771828
Mean0.09075228133
Median Absolute Deviation (MAD)0
Skewness5.426657842
Sum3262
Variance0.1600858598
MonotocityNot monotonic
2020-11-30T23:57:53.297457image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03374978.8%
 
113913.2%
 
25911.4%
 
31730.4%
 
4330.1%
 
55< 0.1%
 
71< 0.1%
 
61< 0.1%
 
(Missing)688916.1%
 
ValueCountFrequency (%) 
03374978.8%
 
113913.2%
 
25911.4%
 
31730.4%
 
4330.1%
 
55< 0.1%
 
61< 0.1%
 
71< 0.1%
 
ValueCountFrequency (%) 
71< 0.1%
 
61< 0.1%
 
55< 0.1%
 
4330.1%
 
31730.4%
 
25911.4%
 
113913.2%
 
03374978.8%
 

ANZ_PERSONEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct14
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean2.02348097
Minimum0
Maximum14
Zeros2730
Zeros (%)6.4%
Memory size334.8 KiB
2020-11-30T23:57:53.386942image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum14
Range14
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.358137211
Coefficient of variation (CV)0.6711885267
Kurtosis1.832487333
Mean2.02348097
Median Absolute Deviation (MAD)1
Skewness1.082769064
Sum72732
Variance1.844536685
MonotocityNot monotonic
2020-11-30T23:57:53.471081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%) 
11203428.1%
 
21074625.1%
 
3553512.9%
 
429516.9%
 
027306.4%
 
512372.9%
 
64851.1%
 
71520.4%
 
8480.1%
 
914< 0.1%
 
108< 0.1%
 
112< 0.1%
 
121< 0.1%
 
141< 0.1%
 
(Missing)688916.1%
 
ValueCountFrequency (%) 
027306.4%
 
11203428.1%
 
21074625.1%
 
3553512.9%
 
429516.9%
 
512372.9%
 
64851.1%
 
71520.4%
 
8480.1%
 
914< 0.1%
 
ValueCountFrequency (%) 
141< 0.1%
 
121< 0.1%
 
112< 0.1%
 
108< 0.1%
 
914< 0.1%
 
8480.1%
 
71520.4%
 
64851.1%
 
512372.9%
 
429516.9%
 

ANZ_STATISTISCHE_HAUSHALTE
Real number (ℝ≥0)

MISSING

Distinct173
Distinct (%)0.5%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean6.33181844
Minimum0
Maximum375
Zeros95
Zeros (%)0.2%
Memory size334.8 KiB
2020-11-30T23:57:53.581751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q37
95-th percentile24
Maximum375
Range375
Interquartile range (IQR)6

Descriptive statistics

Standard deviation14.04551177
Coefficient of variation (CV)2.218242975
Kurtosis110.1963467
Mean6.33181844
Median Absolute Deviation (MAD)1
Skewness8.235406687
Sum222918
Variance197.276401
MonotocityNot monotonic
2020-11-30T23:57:53.699072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
11469734.3%
 
2547912.8%
 
320854.9%
 
414193.3%
 
512923.0%
 
712462.9%
 
612432.9%
 
810932.6%
 
99062.1%
 
106831.6%
 
115881.4%
 
124741.1%
 
133860.9%
 
143120.7%
 
152790.7%
 
162230.5%
 
181700.4%
 
171690.4%
 
191540.4%
 
201100.3%
 
251000.2%
 
22990.2%
 
21980.2%
 
0950.2%
 
24940.2%
 
Other values (148)17124.0%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
0950.2%
 
11469734.3%
 
2547912.8%
 
320854.9%
 
414193.3%
 
512923.0%
 
612432.9%
 
712462.9%
 
810932.6%
 
99062.1%
 
ValueCountFrequency (%) 
3751< 0.1%
 
3541< 0.1%
 
3141< 0.1%
 
2891< 0.1%
 
2841< 0.1%
 
2691< 0.1%
 
2681< 0.1%
 
2621< 0.1%
 
2581< 0.1%
 
2534< 0.1%
 

ANZ_TITEL
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Memory size334.8 KiB
0
35584 
1
 
329
2
 
29
3
 
2
ValueCountFrequency (%) 
03558483.1%
 
13290.8%
 
2290.1%
 
32< 0.1%
 
(Missing)688916.1%
 
2020-11-30T23:57:53.818987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
07152855.7%
 
.3594428.0%
 
n1377810.7%
 
a68895.4%
 
13290.3%
 
229< 0.1%
 
32< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7188855.9%
 
Other Punctuation3594428.0%
 
Lowercase Letter2066716.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
07152899.5%
 
13290.5%
 
229< 0.1%
 
32< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35944100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1377866.7%
 
a688933.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10783283.9%
 
Latin2066716.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
07152866.3%
 
.3594433.3%
 
13290.3%
 
229< 0.1%
 
32< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1377866.7%
 
a688933.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
07152855.7%
 
.3594428.0%
 
n1377810.7%
 
a68895.4%
 
13290.3%
 
229< 0.1%
 
32< 0.1%
 

ARBEIT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7783
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean3.039657632
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:53.905675image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.044241957
Coefficient of variation (CV)0.3435393335
Kurtosis-0.5415108929
Mean3.039657632
Median Absolute Deviation (MAD)1
Skewness-0.3586595221
Sum106540
Variance1.090441265
MonotocityNot monotonic
2020-11-30T23:57:53.988775image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
41220928.5%
 
31122326.2%
 
2684516.0%
 
133847.9%
 
513853.2%
 
94< 0.1%
 
(Missing)778318.2%
 
ValueCountFrequency (%) 
133847.9%
 
2684516.0%
 
31122326.2%
 
41220928.5%
 
513853.2%
 
94< 0.1%
 
ValueCountFrequency (%) 
94< 0.1%
 
513853.2%
 
41220928.5%
 
31122326.2%
 
2684516.0%
 
133847.9%
 

BALLRAUM
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing7641
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean4.286826551
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:54.075588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.185526782
Coefficient of variation (CV)0.5098239353
Kurtosis-1.461158209
Mean4.286826551
Median Absolute Deviation (MAD)2
Skewness-0.3420130215
Sum150862
Variance4.776527316
MonotocityNot monotonic
2020-11-30T23:57:54.152378image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61184227.6%
 
1636614.9%
 
7488411.4%
 
2429110.0%
 
328836.7%
 
426056.1%
 
523215.4%
 
(Missing)764117.8%
 
ValueCountFrequency (%) 
1636614.9%
 
2429110.0%
 
328836.7%
 
426056.1%
 
523215.4%
 
61184227.6%
 
7488411.4%
 
ValueCountFrequency (%) 
7488411.4%
 
61184227.6%
 
523215.4%
 
426056.1%
 
328836.7%
 
2429110.0%
 
1636614.9%
 

CAMEO_DEU_2015
Categorical

MISSING

Distinct45
Distinct (%)0.1%
Missing7740
Missing (%)18.1%
Memory size334.8 KiB
6B
2497 
4C
 
2257
3D
 
2150
2D
 
1994
4A
 
1769
Other values (40)
24426 
ValueCountFrequency (%) 
6B24975.8%
 
4C22575.3%
 
3D21505.0%
 
2D19944.7%
 
4A17694.1%
 
8A16293.8%
 
3C15013.5%
 
8C13233.1%
 
7A12432.9%
 
2C11992.8%
 
6E11412.7%
 
8D11332.6%
 
8B10332.4%
 
2B9202.1%
 
7B8291.9%
 
1D8241.9%
 
5D8131.9%
 
6C6991.6%
 
1A6791.6%
 
9D6621.5%
 
2A5911.4%
 
9B4841.1%
 
5B4591.1%
 
4B4511.1%
 
5C4511.1%
 
Other values (20)636214.9%
 
(Missing)774018.1%
 
2020-11-30T23:57:54.272106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters18
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
n1548016.6%
 
D86069.2%
 
C84949.1%
 
a77408.3%
 
A73257.8%
 
B72607.8%
 
653695.7%
 
452395.6%
 
851185.5%
 
247045.0%
 
343174.6%
 
729973.2%
 
E27963.0%
 
525602.7%
 
924072.6%
 
123752.5%
 
F6050.6%
 
X14< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter3510037.6%
 
Decimal Number3508637.6%
 
Lowercase Letter2322024.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
6536915.3%
 
4523914.9%
 
8511814.6%
 
2470413.4%
 
3431712.3%
 
729978.5%
 
525607.3%
 
924076.9%
 
123756.8%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
D860624.5%
 
C849424.2%
 
A732520.9%
 
B726020.7%
 
E27968.0%
 
F6051.7%
 
X14< 0.1%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1548066.7%
 
a774033.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin5832062.4%
 
Common3508637.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
6536915.3%
 
4523914.9%
 
8511814.6%
 
2470413.4%
 
3431712.3%
 
729978.5%
 
525607.3%
 
924076.9%
 
123756.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1548026.5%
 
D860614.8%
 
C849414.6%
 
a774013.3%
 
A732512.6%
 
B726012.4%
 
E27964.8%
 
F6051.0%
 
X14< 0.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII93406100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
n1548016.6%
 
D86069.2%
 
C84949.1%
 
a77408.3%
 
A73257.8%
 
B72607.8%
 
653695.7%
 
452395.6%
 
851185.5%
 
247045.0%
 
343174.6%
 
729973.2%
 
E27963.0%
 
525602.7%
 
924072.6%
 
123752.5%
 
F6050.6%
 
X14< 0.1%
 

CAMEO_DEUG_2015
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing7747
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean4.967508408
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:54.373946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q37
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.415668768
Coefficient of variation (CV)0.4862938458
Kurtosis-1.201165763
Mean4.967508408
Median Absolute Deviation (MAD)2
Skewness0.04600942768
Sum174290
Variance5.835455596
MonotocityNot monotonic
2020-11-30T23:57:54.457765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
6536912.5%
 
4523912.2%
 
8511811.9%
 
2470411.0%
 
3431710.1%
 
729977.0%
 
525606.0%
 
924075.6%
 
123755.5%
 
(Missing)774718.1%
 
ValueCountFrequency (%) 
123755.5%
 
2470411.0%
 
3431710.1%
 
4523912.2%
 
525606.0%
 
6536912.5%
 
729977.0%
 
8511811.9%
 
924075.6%
 
ValueCountFrequency (%) 
924075.6%
 
8511811.9%
 
729977.0%
 
6536912.5%
 
525606.0%
 
4523912.2%
 
3431710.1%
 
2470411.0%
 
123755.5%
 

CAMEO_INTL_2015
Real number (ℝ≥0)

MISSING

Distinct21
Distinct (%)0.1%
Missing7747
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean32.86607194
Minimum12
Maximum55
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:54.555806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile13
Q122
median32
Q345
95-th percentile54
Maximum55
Range43
Interquartile range (IQR)23

Descriptive statistics

Standard deviation14.14035759
Coefficient of variation (CV)0.430241789
Kurtosis-1.391863978
Mean32.86607194
Median Absolute Deviation (MAD)11
Skewness0.07911466035
Sum1153139
Variance199.9497128
MonotocityNot monotonic
2020-11-30T23:57:54.645728image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%) 
2441949.8%
 
1437348.7%
 
5132047.5%
 
4131057.2%
 
4324975.8%
 
2524765.8%
 
4519504.6%
 
5418434.3%
 
2217694.1%
 
1315993.7%
 
5515363.6%
 
1511552.7%
 
2311172.6%
 
3410032.3%
 
446991.6%
 
316751.6%
 
356001.4%
 
125911.4%
 
324591.1%
 
334511.1%
 
524291.0%
 
(Missing)774718.1%
 
ValueCountFrequency (%) 
125911.4%
 
1315993.7%
 
1437348.7%
 
1511552.7%
 
2217694.1%
 
2311172.6%
 
2441949.8%
 
2524765.8%
 
316751.6%
 
324591.1%
 
ValueCountFrequency (%) 
5515363.6%
 
5418434.3%
 
524291.0%
 
5132047.5%
 
4519504.6%
 
446991.6%
 
4324975.8%
 
4131057.2%
 
356001.4%
 
3410032.3%
 

CJT_GESAMTTYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean3.31771388
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:54.729074image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.760697085
Coefficient of variation (CV)0.5306958792
Kurtosis-1.311595239
Mean3.31771388
Median Absolute Deviation (MAD)1
Skewness0.3069180133
Sum140190
Variance3.100054224
MonotocityNot monotonic
2020-11-30T23:57:54.814000image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21271729.7%
 
6824419.2%
 
1646215.1%
 
4617414.4%
 
3457810.7%
 
540809.5%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
1646215.1%
 
21271729.7%
 
3457810.7%
 
4617414.4%
 
540809.5%
 
6824419.2%
 
ValueCountFrequency (%) 
6824419.2%
 
540809.5%
 
4617414.4%
 
3457810.7%
 
21271729.7%
 
1646215.1%
 

CJT_KATALOGNUTZER
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean3.884084724
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:54.898301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.451494391
Coefficient of variation (CV)0.3737030715
Kurtosis-0.5278070885
Mean3.884084724
Median Absolute Deviation (MAD)0
Skewness-0.972648208
Sum164122
Variance2.106835968
MonotocityNot monotonic
2020-11-30T23:57:54.978466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52270953.0%
 
4591313.8%
 
1566313.2%
 
3532212.4%
 
226486.2%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
1566313.2%
 
226486.2%
 
3532212.4%
 
4591313.8%
 
52270953.0%
 
ValueCountFrequency (%) 
52270953.0%
 
4591313.8%
 
3532212.4%
 
226486.2%
 
1566313.2%
 

CJT_TYP_1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean2.540030766
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:55.067023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.349703024
Coefficient of variation (CV)0.531372707
Kurtosis-0.6720326876
Mean2.540030766
Median Absolute Deviation (MAD)1
Skewness0.7432984473
Sum107329
Variance1.821698252
MonotocityNot monotonic
2020-11-30T23:57:55.151572image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21739040.6%
 
1939121.9%
 
5711216.6%
 
3585013.7%
 
425125.9%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
1939121.9%
 
21739040.6%
 
3585013.7%
 
425125.9%
 
5711216.6%
 
ValueCountFrequency (%) 
5711216.6%
 
425125.9%
 
3585013.7%
 
21739040.6%
 
1939121.9%
 

CJT_TYP_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean2.305194652
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:55.243830image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.386515961
Coefficient of variation (CV)0.6014745697
Kurtosis-0.454935537
Mean2.305194652
Median Absolute Deviation (MAD)1
Skewness0.9114743015
Sum97406
Variance1.92242651
MonotocityNot monotonic
2020-11-30T23:57:55.331354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11494134.9%
 
21431033.4%
 
5636114.9%
 
3453210.6%
 
421114.9%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
11494134.9%
 
21431033.4%
 
3453210.6%
 
421114.9%
 
5636114.9%
 
ValueCountFrequency (%) 
5636114.9%
 
421114.9%
 
3453210.6%
 
21431033.4%
 
11494134.9%
 

CJT_TYP_3
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean4.468204946
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:55.422005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9240202627
Coefficient of variation (CV)0.2067989884
Kurtosis2.40182846
Mean4.468204946
Median Absolute Deviation (MAD)0
Skewness-1.770106063
Sum188804
Variance0.8538134459
MonotocityNot monotonic
2020-11-30T23:57:55.504758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52911868.0%
 
4672815.7%
 
340039.3%
 
218874.4%
 
15191.2%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
15191.2%
 
218874.4%
 
340039.3%
 
4672815.7%
 
52911868.0%
 
ValueCountFrequency (%) 
52911868.0%
 
4672815.7%
 
340039.3%
 
218874.4%
 
15191.2%
 

CJT_TYP_4
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean4.371719323
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:55.594863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.06140354
Coefficient of variation (CV)0.242788583
Kurtosis1.756630451
Mean4.371719323
Median Absolute Deviation (MAD)0
Skewness-1.667984301
Sum184727
Variance1.126577474
MonotocityNot monotonic
2020-11-30T23:57:55.676601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52825166.0%
 
4665215.5%
 
332917.7%
 
229306.8%
 
111312.6%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
111312.6%
 
229306.8%
 
332917.7%
 
4665215.5%
 
52825166.0%
 
ValueCountFrequency (%) 
52825166.0%
 
4665215.5%
 
332917.7%
 
229306.8%
 
111312.6%
 

CJT_TYP_5
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean4.461696841
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:55.767478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9457494892
Coefficient of variation (CV)0.2119708091
Kurtosis2.448902342
Mean4.461696841
Median Absolute Deviation (MAD)0
Skewness-1.77510665
Sum188529
Variance0.8944420963
MonotocityNot monotonic
2020-11-30T23:57:55.850732image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52947968.8%
 
4575013.4%
 
3481411.2%
 
214803.5%
 
17321.7%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
17321.7%
 
214803.5%
 
3481411.2%
 
4575013.4%
 
52947968.8%
 
ValueCountFrequency (%) 
52947968.8%
 
4575013.4%
 
3481411.2%
 
214803.5%
 
17321.7%
 

CJT_TYP_6
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean4.424375814
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:55.946134image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9807646493
Coefficient of variation (CV)0.2216729977
Kurtosis2.168700016
Mean4.424375814
Median Absolute Deviation (MAD)0
Skewness-1.734768484
Sum186952
Variance0.9618992974
MonotocityNot monotonic
2020-11-30T23:57:56.028313image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52847166.5%
 
4713816.7%
 
334828.1%
 
224355.7%
 
17291.7%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
17291.7%
 
224355.7%
 
334828.1%
 
4713816.7%
 
52847166.5%
 
ValueCountFrequency (%) 
52847166.5%
 
4713816.7%
 
334828.1%
 
224355.7%
 
17291.7%
 

D19_BANKEN_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1028646137
Minimum0
Maximum6
Zeros40055
Zeros (%)93.5%
Memory size334.8 KiB
2020-11-30T23:57:56.115643image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.45825906
Coefficient of variation (CV)4.454972836
Kurtosis42.00842379
Mean0.1028646137
Median Absolute Deviation (MAD)0
Skewness5.88382803
Sum4406
Variance0.2100013661
MonotocityNot monotonic
2020-11-30T23:57:56.196123image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
04005593.5%
 
117484.1%
 
26671.6%
 
31790.4%
 
41420.3%
 
5330.1%
 
69< 0.1%
 
ValueCountFrequency (%) 
04005593.5%
 
117484.1%
 
26671.6%
 
31790.4%
 
41420.3%
 
5330.1%
 
69< 0.1%
 
ValueCountFrequency (%) 
69< 0.1%
 
5330.1%
 
41420.3%
 
31790.4%
 
26671.6%
 
117484.1%
 
04005593.5%
 

D19_BANKEN_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1763360026
Minimum0
Maximum6
Zeros38560
Zeros (%)90.0%
Memory size334.8 KiB
2020-11-30T23:57:56.282986image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6344151536
Coefficient of variation (CV)3.597763044
Kurtosis25.33674889
Mean0.1763360026
Median Absolute Deviation (MAD)0
Skewness4.669833815
Sum7553
Variance0.4024825871
MonotocityNot monotonic
2020-11-30T23:57:56.363958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03856090.0%
 
123885.6%
 
211152.6%
 
33230.8%
 
43000.7%
 
51160.3%
 
6310.1%
 
ValueCountFrequency (%) 
03856090.0%
 
123885.6%
 
211152.6%
 
33230.8%
 
43000.7%
 
51160.3%
 
6310.1%
 
ValueCountFrequency (%) 
6310.1%
 
51160.3%
 
43000.7%
 
33230.8%
 
211152.6%
 
123885.6%
 
03856090.0%
 

D19_BANKEN_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.336352812
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:56.455198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.655615276
Coefficient of variation (CV)0.1773299819
Kurtosis8.88961265
Mean9.336352812
Median Absolute Deviation (MAD)0
Skewness-2.983080902
Sum399904
Variance2.741061941
MonotocityNot monotonic
2020-11-30T23:57:56.535801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103361678.5%
 
935268.2%
 
516603.9%
 
814183.3%
 
77781.8%
 
67171.7%
 
13610.8%
 
22910.7%
 
42770.6%
 
31890.4%
 
ValueCountFrequency (%) 
13610.8%
 
22910.7%
 
31890.4%
 
42770.6%
 
516603.9%
 
67171.7%
 
77781.8%
 
814183.3%
 
935268.2%
 
103361678.5%
 
ValueCountFrequency (%) 
103361678.5%
 
935268.2%
 
814183.3%
 
77781.8%
 
67171.7%
 
516603.9%
 
42770.6%
 
31890.4%
 
22910.7%
 
13610.8%
 

D19_BANKEN_DIREKT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7035696776
Minimum0
Maximum7
Zeros36690
Zeros (%)85.7%
Memory size334.8 KiB
2020-11-30T23:57:56.618140image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.821388153
Coefficient of variation (CV)2.588781483
Kurtosis4.001366773
Mean0.7035696776
Median Absolute Deviation (MAD)0
Skewness2.381921294
Sum30136
Variance3.317454805
MonotocityNot monotonic
2020-11-30T23:57:56.699598image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03669085.7%
 
631287.3%
 
311972.8%
 
57331.7%
 
73270.8%
 
42690.6%
 
22580.6%
 
12310.5%
 
ValueCountFrequency (%) 
03669085.7%
 
12310.5%
 
22580.6%
 
311972.8%
 
42690.6%
 
57331.7%
 
631287.3%
 
73270.8%
 
ValueCountFrequency (%) 
73270.8%
 
631287.3%
 
57331.7%
 
42690.6%
 
311972.8%
 
22580.6%
 
12310.5%
 
03669085.7%
 

D19_BANKEN_GROSS
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4504937782
Minimum0
Maximum6
Zeros38753
Zeros (%)90.5%
Memory size334.8 KiB
2020-11-30T23:57:56.787019image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.469663282
Coefficient of variation (CV)3.262338689
Kurtosis8.46663348
Mean0.4504937782
Median Absolute Deviation (MAD)0
Skewness3.165206547
Sum19296
Variance2.159910162
MonotocityNot monotonic
2020-11-30T23:57:56.870004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03875390.5%
 
620824.9%
 
38602.0%
 
55651.3%
 
42230.5%
 
11930.5%
 
21570.4%
 
ValueCountFrequency (%) 
03875390.5%
 
11930.5%
 
21570.4%
 
38602.0%
 
42230.5%
 
55651.3%
 
620824.9%
 
ValueCountFrequency (%) 
620824.9%
 
55651.3%
 
42230.5%
 
38602.0%
 
21570.4%
 
11930.5%
 
03875390.5%
 

D19_BANKEN_LOKAL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1155417552
Minimum0
Maximum7
Zeros41978
Zeros (%)98.0%
Memory size334.8 KiB
2020-11-30T23:57:56.959570image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8381207501
Coefficient of variation (CV)7.253834328
Kurtosis54.34879809
Mean0.1155417552
Median Absolute Deviation (MAD)0
Skewness7.415353142
Sum4949
Variance0.7024463918
MonotocityNot monotonic
2020-11-30T23:57:57.044283image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
04197898.0%
 
73980.9%
 
62290.5%
 
31650.4%
 
5550.1%
 
25< 0.1%
 
42< 0.1%
 
11< 0.1%
 
ValueCountFrequency (%) 
04197898.0%
 
11< 0.1%
 
25< 0.1%
 
31650.4%
 
42< 0.1%
 
5550.1%
 
62290.5%
 
73980.9%
 
ValueCountFrequency (%) 
73980.9%
 
62290.5%
 
5550.1%
 
42< 0.1%
 
31650.4%
 
25< 0.1%
 
11< 0.1%
 
04197898.0%
 

D19_BANKEN_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.846006584
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:57.138023image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.8418601471
Coefficient of variation (CV)0.0855027
Kurtosis39.0718492
Mean9.846006584
Median Absolute Deviation (MAD)0
Skewness-6.09917614
Sum421734
Variance0.7087285073
MonotocityNot monotonic
2020-11-30T23:57:57.220272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
104105495.8%
 
58632.0%
 
84481.0%
 
93000.7%
 
2640.1%
 
6480.1%
 
1220.1%
 
419< 0.1%
 
79< 0.1%
 
36< 0.1%
 
ValueCountFrequency (%) 
1220.1%
 
2640.1%
 
36< 0.1%
 
419< 0.1%
 
58632.0%
 
6480.1%
 
79< 0.1%
 
84481.0%
 
93000.7%
 
104105495.8%
 
ValueCountFrequency (%) 
104105495.8%
 
93000.7%
 
84481.0%
 
79< 0.1%
 
6480.1%
 
58632.0%
 
419< 0.1%
 
36< 0.1%
 
2640.1%
 
1220.1%
 

D19_BANKEN_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.574020031
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:57.307916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.376190773
Coefficient of variation (CV)0.1437422074
Kurtosis17.61057419
Mean9.574020031
Median Absolute Deviation (MAD)0
Skewness-4.068583261
Sum410084
Variance1.893901043
MonotocityNot monotonic
2020-11-30T23:57:57.388482image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103672785.7%
 
925796.0%
 
88281.9%
 
57251.7%
 
76291.5%
 
65031.2%
 
13060.7%
 
42010.5%
 
21820.4%
 
31530.4%
 
ValueCountFrequency (%) 
13060.7%
 
21820.4%
 
31530.4%
 
42010.5%
 
57251.7%
 
65031.2%
 
76291.5%
 
88281.9%
 
925796.0%
 
103672785.7%
 
ValueCountFrequency (%) 
103672785.7%
 
925796.0%
 
88281.9%
 
76291.5%
 
65031.2%
 
57251.7%
 
42010.5%
 
31530.4%
 
21820.4%
 
13060.7%
 

D19_BANKEN_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct10
Distinct (%)< 0.1%
Missing7526
Missing (%)17.6%
Infinite0
Infinite (%)0.0%
Mean0.4303395927
Minimum0
Maximum10
Zeros33740
Zeros (%)78.8%
Memory size334.8 KiB
2020-11-30T23:57:57.475012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum10
Range10
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.012377579
Coefficient of variation (CV)4.676254783
Kurtosis18.3235359
Mean0.4303395927
Median Absolute Deviation (MAD)0
Skewness4.498076185
Sum15194
Variance4.04966352
MonotocityNot monotonic
2020-11-30T23:57:57.563817image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
03374078.8%
 
1014523.4%
 
5420.1%
 
7270.1%
 
817< 0.1%
 
316< 0.1%
 
97< 0.1%
 
63< 0.1%
 
42< 0.1%
 
21< 0.1%
 
(Missing)752617.6%
 
ValueCountFrequency (%) 
03374078.8%
 
21< 0.1%
 
316< 0.1%
 
42< 0.1%
 
5420.1%
 
63< 0.1%
 
7270.1%
 
817< 0.1%
 
97< 0.1%
 
1014523.4%
 
ValueCountFrequency (%) 
1014523.4%
 
97< 0.1%
 
817< 0.1%
 
7270.1%
 
63< 0.1%
 
5420.1%
 
42< 0.1%
 
316< 0.1%
 
21< 0.1%
 
03374078.8%
 

D19_BANKEN_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3896528378
Minimum0
Maximum7
Zeros39736
Zeros (%)92.8%
Memory size334.8 KiB
2020-11-30T23:57:57.651385image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.438006494
Coefficient of variation (CV)3.690481255
Kurtosis10.82117563
Mean0.3896528378
Median Absolute Deviation (MAD)0
Skewness3.540633076
Sum16690
Variance2.067862676
MonotocityNot monotonic
2020-11-30T23:57:57.737620image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03973692.8%
 
620914.9%
 
33510.8%
 
53200.7%
 
71510.4%
 
2970.2%
 
4510.1%
 
1360.1%
 
ValueCountFrequency (%) 
03973692.8%
 
1360.1%
 
2970.2%
 
33510.8%
 
4510.1%
 
53200.7%
 
620914.9%
 
71510.4%
 
ValueCountFrequency (%) 
71510.4%
 
620914.9%
 
53200.7%
 
4510.1%
 
33510.8%
 
2970.2%
 
1360.1%
 
03973692.8%
 

D19_BEKLEIDUNG_GEH
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8344267271
Minimum0
Maximum7
Zeros35744
Zeros (%)83.4%
Memory size334.8 KiB
2020-11-30T23:57:57.828311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.967658249
Coefficient of variation (CV)2.358095907
Kurtosis2.668044582
Mean0.8344267271
Median Absolute Deviation (MAD)0
Skewness2.093073163
Sum35741
Variance3.871678986
MonotocityNot monotonic
2020-11-30T23:57:57.912410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03574483.4%
 
635518.3%
 
314913.5%
 
510282.4%
 
75071.2%
 
22300.5%
 
41770.4%
 
11050.2%
 
ValueCountFrequency (%) 
03574483.4%
 
11050.2%
 
22300.5%
 
314913.5%
 
41770.4%
 
510282.4%
 
635518.3%
 
75071.2%
 
ValueCountFrequency (%) 
75071.2%
 
635518.3%
 
510282.4%
 
41770.4%
 
314913.5%
 
22300.5%
 
11050.2%
 
03574483.4%
 

D19_BEKLEIDUNG_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.654308594
Minimum0
Maximum7
Zeros29888
Zeros (%)69.8%
Memory size334.8 KiB
2020-11-30T23:57:58.001267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.632243583
Coefficient of variation (CV)1.591144235
Kurtosis-0.7223492117
Mean1.654308594
Median Absolute Deviation (MAD)0
Skewness1.066766895
Sum70859
Variance6.928706279
MonotocityNot monotonic
2020-11-30T23:57:58.083478image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02988869.8%
 
6767817.9%
 
719614.6%
 
316893.9%
 
58622.0%
 
23350.8%
 
12210.5%
 
41990.5%
 
ValueCountFrequency (%) 
02988869.8%
 
12210.5%
 
23350.8%
 
316893.9%
 
41990.5%
 
58622.0%
 
6767817.9%
 
719614.6%
 
ValueCountFrequency (%) 
719614.6%
 
6767817.9%
 
58622.0%
 
41990.5%
 
316893.9%
 
23350.8%
 
12210.5%
 
02988869.8%
 

D19_BILDUNG
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.029976887
Minimum0
Maximum7
Zeros34643
Zeros (%)80.9%
Memory size334.8 KiB
2020-11-30T23:57:58.170665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.240404714
Coefficient of variation (CV)2.175199019
Kurtosis1.61414115
Mean1.029976887
Median Absolute Deviation (MAD)0
Skewness1.850324596
Sum44117
Variance5.019413282
MonotocityNot monotonic
2020-11-30T23:57:58.252627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03464380.9%
 
6428210.0%
 
717414.1%
 
29652.3%
 
35771.3%
 
53830.9%
 
41400.3%
 
11020.2%
 
ValueCountFrequency (%) 
03464380.9%
 
11020.2%
 
29652.3%
 
35771.3%
 
41400.3%
 
53830.9%
 
6428210.0%
 
717414.1%
 
ValueCountFrequency (%) 
717414.1%
 
6428210.0%
 
53830.9%
 
41400.3%
 
35771.3%
 
29652.3%
 
11020.2%
 
03464380.9%
 

D19_BIO_OEKO
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6432190134
Minimum0
Maximum7
Zeros38272
Zeros (%)89.4%
Memory size334.8 KiB
2020-11-30T23:57:58.341068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.887005043
Coefficient of variation (CV)2.933689775
Kurtosis5.143030923
Mean0.6432190134
Median Absolute Deviation (MAD)0
Skewness2.647410172
Sum27551
Variance3.560788031
MonotocityNot monotonic
2020-11-30T23:57:58.424745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03827289.4%
 
628756.7%
 
712002.8%
 
32500.6%
 
52210.5%
 
49< 0.1%
 
24< 0.1%
 
12< 0.1%
 
ValueCountFrequency (%) 
03827289.4%
 
12< 0.1%
 
24< 0.1%
 
32500.6%
 
49< 0.1%
 
52210.5%
 
628756.7%
 
712002.8%
 
ValueCountFrequency (%) 
712002.8%
 
628756.7%
 
52210.5%
 
49< 0.1%
 
32500.6%
 
24< 0.1%
 
12< 0.1%
 
03827289.4%
 

D19_BUCH_CD
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.527653912
Minimum0
Maximum7
Zeros22306
Zeros (%)52.1%
Memory size334.8 KiB
2020-11-30T23:57:58.514543image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.835753728
Coefficient of variation (CV)1.121891614
Kurtosis-1.779218516
Mean2.527653912
Median Absolute Deviation (MAD)0
Skewness0.3401589186
Sum108267
Variance8.041499205
MonotocityNot monotonic
2020-11-30T23:57:58.591552image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02230652.1%
 
61457234.0%
 
317684.1%
 
511042.6%
 
110832.5%
 
77561.8%
 
26701.6%
 
45741.3%
 
ValueCountFrequency (%) 
02230652.1%
 
110832.5%
 
26701.6%
 
317684.1%
 
45741.3%
 
511042.6%
 
61457234.0%
 
77561.8%
 
ValueCountFrequency (%) 
77561.8%
 
61457234.0%
 
511042.6%
 
45741.3%
 
317684.1%
 
26701.6%
 
110832.5%
 
02230652.1%
 

D19_DIGIT_SERV
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1965307123
Minimum0
Maximum7
Zeros41122
Zeros (%)96.0%
Memory size334.8 KiB
2020-11-30T23:57:58.674608image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.010816599
Coefficient of variation (CV)5.143300951
Kurtosis26.6660553
Mean0.1965307123
Median Absolute Deviation (MAD)0
Skewness5.254858016
Sum8418
Variance1.021750198
MonotocityNot monotonic
2020-11-30T23:57:58.758617image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
04112296.0%
 
68552.0%
 
34201.0%
 
52120.5%
 
7990.2%
 
2840.2%
 
4220.1%
 
119< 0.1%
 
ValueCountFrequency (%) 
04112296.0%
 
119< 0.1%
 
2840.2%
 
34201.0%
 
4220.1%
 
52120.5%
 
68552.0%
 
7990.2%
 
ValueCountFrequency (%) 
7990.2%
 
68552.0%
 
52120.5%
 
4220.1%
 
34201.0%
 
2840.2%
 
119< 0.1%
 
04112296.0%
 

D19_DROGERIEARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6787056709
Minimum0
Maximum7
Zeros36583
Zeros (%)85.4%
Memory size334.8 KiB
2020-11-30T23:57:58.848419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.762041312
Coefficient of variation (CV)2.596178855
Kurtosis4.443043482
Mean0.6787056709
Median Absolute Deviation (MAD)0
Skewness2.446411718
Sum29071
Variance3.104789584
MonotocityNot monotonic
2020-11-30T23:57:58.933871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03658385.4%
 
624255.7%
 
312993.0%
 
59032.1%
 
24661.1%
 
44481.0%
 
74461.0%
 
12630.6%
 
ValueCountFrequency (%) 
03658385.4%
 
12630.6%
 
24661.1%
 
312993.0%
 
44481.0%
 
59032.1%
 
624255.7%
 
74461.0%
 
ValueCountFrequency (%) 
74461.0%
 
624255.7%
 
59032.1%
 
44481.0%
 
312993.0%
 
24661.1%
 
12630.6%
 
03658385.4%
 

D19_ENERGIE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4156141293
Minimum0
Maximum7
Zeros39059
Zeros (%)91.2%
Memory size334.8 KiB
2020-11-30T23:57:59.023128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.419694092
Coefficient of variation (CV)3.415894677
Kurtosis10.46116938
Mean0.4156141293
Median Absolute Deviation (MAD)0
Skewness3.417850762
Sum17802
Variance2.015531315
MonotocityNot monotonic
2020-11-30T23:57:59.107043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03905991.2%
 
612663.0%
 
311982.8%
 
56231.5%
 
74091.0%
 
21520.4%
 
4680.2%
 
1580.1%
 
ValueCountFrequency (%) 
03905991.2%
 
1580.1%
 
21520.4%
 
311982.8%
 
4680.2%
 
56231.5%
 
612663.0%
 
74091.0%
 
ValueCountFrequency (%) 
74091.0%
 
612663.0%
 
56231.5%
 
4680.2%
 
311982.8%
 
21520.4%
 
1580.1%
 
03905991.2%
 

D19_FREIZEIT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6065183387
Minimum0
Maximum7
Zeros37632
Zeros (%)87.9%
Memory size334.8 KiB
2020-11-30T23:57:59.196958image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.709284481
Coefficient of variation (CV)2.818190931
Kurtosis5.30230646
Mean0.6065183387
Median Absolute Deviation (MAD)0
Skewness2.636672237
Sum25979
Variance2.921653439
MonotocityNot monotonic
2020-11-30T23:57:59.278727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03763287.9%
 
627566.4%
 
310932.6%
 
56751.6%
 
72320.5%
 
22220.5%
 
41660.4%
 
1570.1%
 
ValueCountFrequency (%) 
03763287.9%
 
1570.1%
 
22220.5%
 
310932.6%
 
41660.4%
 
56751.6%
 
627566.4%
 
72320.5%
 
ValueCountFrequency (%) 
72320.5%
 
627566.4%
 
56751.6%
 
41660.4%
 
310932.6%
 
22220.5%
 
1570.1%
 
03763287.9%
 

D19_GARTEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4051549039
Minimum0
Maximum7
Zeros39649
Zeros (%)92.6%
Memory size334.8 KiB
2020-11-30T23:57:59.367039image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.467021212
Coefficient of variation (CV)3.620889685
Kurtosis10.36046271
Mean0.4051549039
Median Absolute Deviation (MAD)0
Skewness3.468296275
Sum17354
Variance2.152151237
MonotocityNot monotonic
2020-11-30T23:57:59.451201image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03964992.6%
 
618384.3%
 
55421.3%
 
34261.0%
 
73080.7%
 
2310.1%
 
4270.1%
 
112< 0.1%
 
ValueCountFrequency (%) 
03964992.6%
 
112< 0.1%
 
2310.1%
 
34261.0%
 
4270.1%
 
55421.3%
 
618384.3%
 
73080.7%
 
ValueCountFrequency (%) 
73080.7%
 
618384.3%
 
55421.3%
 
4270.1%
 
34261.0%
 
2310.1%
 
112< 0.1%
 
03964992.6%
 

D19_GESAMT_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9599140849
Minimum0
Maximum6
Zeros25068
Zeros (%)58.5%
Memory size334.8 KiB
2020-11-30T23:57:59.540137image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.421690237
Coefficient of variation (CV)1.481059878
Kurtosis1.253939463
Mean0.9599140849
Median Absolute Deviation (MAD)0
Skewness1.466321916
Sum41116
Variance2.02120313
MonotocityNot monotonic
2020-11-30T23:57:59.616396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02506858.5%
 
1614914.4%
 
2537512.5%
 
425075.9%
 
323705.5%
 
511052.6%
 
62590.6%
 
ValueCountFrequency (%) 
02506858.5%
 
1614914.4%
 
2537512.5%
 
323705.5%
 
425075.9%
 
511052.6%
 
62590.6%
 
ValueCountFrequency (%) 
62590.6%
 
511052.6%
 
425075.9%
 
323705.5%
 
2537512.5%
 
1614914.4%
 
02506858.5%
 

D19_GESAMT_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.451871221
Minimum0
Maximum6
Zeros20500
Zeros (%)47.9%
Memory size334.8 KiB
2020-11-30T23:57:59.699146image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.774891236
Coefficient of variation (CV)1.222485308
Kurtosis-0.215284834
Mean1.451871221
Median Absolute Deviation (MAD)1
Skewness0.9929507687
Sum62188
Variance3.150238899
MonotocityNot monotonic
2020-11-30T23:57:59.781509image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02050047.9%
 
2607714.2%
 
1558213.0%
 
437918.9%
 
331667.4%
 
525125.9%
 
612052.8%
 
ValueCountFrequency (%) 
02050047.9%
 
1558213.0%
 
2607714.2%
 
331667.4%
 
437918.9%
 
525125.9%
 
612052.8%
 
ValueCountFrequency (%) 
612052.8%
 
525125.9%
 
437918.9%
 
331667.4%
 
2607714.2%
 
1558213.0%
 
02050047.9%
 

D19_GESAMT_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.526790092
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:57:59.872474image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.172484798
Coefficient of variation (CV)0.4860712163
Kurtosis-1.266568028
Mean6.526790092
Median Absolute Deviation (MAD)3
Skewness-0.390484015
Sum279562
Variance10.0646598
MonotocityNot monotonic
2020-11-30T23:57:59.955116image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101196827.9%
 
5594613.9%
 
9567313.2%
 
139479.2%
 
234198.0%
 
828596.7%
 
425135.9%
 
624105.6%
 
721585.0%
 
319404.5%
 
ValueCountFrequency (%) 
139479.2%
 
234198.0%
 
319404.5%
 
425135.9%
 
5594613.9%
 
624105.6%
 
721585.0%
 
828596.7%
 
9567313.2%
 
101196827.9%
 
ValueCountFrequency (%) 
101196827.9%
 
9567313.2%
 
828596.7%
 
721585.0%
 
624105.6%
 
5594613.9%
 
425135.9%
 
319404.5%
 
234198.0%
 
139479.2%
 

D19_GESAMT_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.198608549
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:00.041871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q17
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.321973998
Coefficient of variation (CV)0.2832156194
Kurtosis1.004831311
Mean8.198608549
Median Absolute Deviation (MAD)1
Skewness-1.375764227
Sum351171
Variance5.391563249
MonotocityNot monotonic
2020-11-30T23:58:00.123431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101779841.6%
 
9947822.1%
 
841379.7%
 
540359.4%
 
721495.0%
 
618074.2%
 
210662.5%
 
49842.3%
 
17361.7%
 
36431.5%
 
ValueCountFrequency (%) 
17361.7%
 
210662.5%
 
36431.5%
 
49842.3%
 
540359.4%
 
618074.2%
 
721495.0%
 
841379.7%
 
9947822.1%
 
101779841.6%
 
ValueCountFrequency (%) 
101779841.6%
 
9947822.1%
 
841379.7%
 
721495.0%
 
618074.2%
 
540359.4%
 
49842.3%
 
36431.5%
 
210662.5%
 
17361.7%
 

D19_GESAMT_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.557303948
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:00.211432image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.023293941
Coefficient of variation (CV)0.4000492718
Kurtosis-0.5693230136
Mean7.557303948
Median Absolute Deviation (MAD)1
Skewness-0.9227882261
Sum323702
Variance9.140306254
MonotocityNot monotonic
2020-11-30T23:58:00.294274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101976846.2%
 
9501211.7%
 
542269.9%
 
126726.2%
 
821835.1%
 
220524.8%
 
619474.5%
 
418274.3%
 
717794.2%
 
313673.2%
 
ValueCountFrequency (%) 
126726.2%
 
220524.8%
 
313673.2%
 
418274.3%
 
542269.9%
 
619474.5%
 
717794.2%
 
821835.1%
 
9501211.7%
 
101976846.2%
 
ValueCountFrequency (%) 
101976846.2%
 
9501211.7%
 
821835.1%
 
717794.2%
 
619474.5%
 
542269.9%
 
418274.3%
 
313673.2%
 
220524.8%
 
126726.2%
 

D19_GESAMT_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing7526
Missing (%)17.6%
Infinite0
Infinite (%)0.0%
Mean2.929362449
Minimum0
Maximum10
Zeros23181
Zeros (%)54.1%
Memory size334.8 KiB
2020-11-30T23:58:00.382402image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q38
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.309480951
Coefficient of variation (CV)1.471132721
Kurtosis-1.083319447
Mean2.929362449
Median Absolute Deviation (MAD)0
Skewness0.8967216415
Sum103427
Variance18.57162607
MonotocityNot monotonic
2020-11-30T23:58:00.466995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
02318154.1%
 
10822719.2%
 
510062.3%
 
86001.4%
 
75821.4%
 
35151.2%
 
93480.8%
 
12620.6%
 
22170.5%
 
62020.5%
 
41670.4%
 
(Missing)752617.6%
 
ValueCountFrequency (%) 
02318154.1%
 
12620.6%
 
22170.5%
 
35151.2%
 
41670.4%
 
510062.3%
 
62020.5%
 
75821.4%
 
86001.4%
 
93480.8%
 
ValueCountFrequency (%) 
10822719.2%
 
93480.8%
 
86001.4%
 
75821.4%
 
62020.5%
 
510062.3%
 
41670.4%
 
35151.2%
 
22170.5%
 
12620.6%
 

D19_HANDWERK
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.72381108
Minimum0
Maximum7
Zeros30723
Zeros (%)71.7%
Memory size334.8 KiB
2020-11-30T23:58:00.547447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.764528831
Coefficient of variation (CV)1.603730747
Kurtosis-0.9497943579
Mean1.72381108
Median Absolute Deviation (MAD)0
Skewness1.003091992
Sum73836
Variance7.642619655
MonotocityNot monotonic
2020-11-30T23:58:00.636797image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03072371.7%
 
6952122.2%
 
721275.0%
 
32350.5%
 
52180.5%
 
25< 0.1%
 
44< 0.1%
 
ValueCountFrequency (%) 
03072371.7%
 
25< 0.1%
 
32350.5%
 
44< 0.1%
 
52180.5%
 
6952122.2%
 
721275.0%
 
ValueCountFrequency (%) 
721275.0%
 
6952122.2%
 
52180.5%
 
44< 0.1%
 
32350.5%
 
25< 0.1%
 
03072371.7%
 

D19_HAUS_DEKO
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.635678099
Minimum0
Maximum7
Zeros28399
Zeros (%)66.3%
Memory size334.8 KiB
2020-11-30T23:58:00.725528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.479792052
Coefficient of variation (CV)1.516063615
Kurtosis-0.7675388329
Mean1.635678099
Median Absolute Deviation (MAD)0
Skewness1.018576796
Sum70061
Variance6.14936862
MonotocityNot monotonic
2020-11-30T23:58:00.806495image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02839966.3%
 
6799218.7%
 
327686.5%
 
515303.6%
 
27561.8%
 
16601.5%
 
43710.9%
 
73570.8%
 
ValueCountFrequency (%) 
02839966.3%
 
16601.5%
 
27561.8%
 
327686.5%
 
43710.9%
 
515303.6%
 
6799218.7%
 
73570.8%
 
ValueCountFrequency (%) 
73570.8%
 
6799218.7%
 
515303.6%
 
43710.9%
 
327686.5%
 
27561.8%
 
16601.5%
 
02839966.3%
 

D19_KINDERARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.168164733
Minimum0
Maximum7
Zeros33680
Zeros (%)78.6%
Memory size334.8 KiB
2020-11-30T23:58:00.892794image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.34102151
Coefficient of variation (CV)2.004016595
Kurtosis0.7972043708
Mean1.168164733
Median Absolute Deviation (MAD)0
Skewness1.619165578
Sum50036
Variance5.480381711
MonotocityNot monotonic
2020-11-30T23:58:00.976037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03368078.6%
 
6497511.6%
 
716763.9%
 
311702.7%
 
56761.6%
 
23320.8%
 
41920.4%
 
11320.3%
 
ValueCountFrequency (%) 
03368078.6%
 
11320.3%
 
23320.8%
 
311702.7%
 
41920.4%
 
56761.6%
 
6497511.6%
 
716763.9%
 
ValueCountFrequency (%) 
716763.9%
 
6497511.6%
 
56761.6%
 
41920.4%
 
311702.7%
 
23320.8%
 
11320.3%
 
03368078.6%
 

D19_KONSUMTYP
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing7526
Missing (%)17.6%
Infinite0
Infinite (%)0.0%
Mean3.681394624
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:01.064874image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.751108952
Coefficient of variation (CV)0.7473007469
Kurtosis-0.2409523378
Mean3.681394624
Median Absolute Deviation (MAD)1
Skewness1.081196607
Sum129979
Variance7.568600468
MonotocityNot monotonic
2020-11-30T23:58:01.153319image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31150226.9%
 
1775718.1%
 
9635014.8%
 
2596813.9%
 
415973.7%
 
615773.7%
 
55561.3%
 
(Missing)752617.6%
 
ValueCountFrequency (%) 
1775718.1%
 
2596813.9%
 
31150226.9%
 
415973.7%
 
55561.3%
 
615773.7%
 
9635014.8%
 
ValueCountFrequency (%) 
9635014.8%
 
615773.7%
 
55561.3%
 
415973.7%
 
31150226.9%
 
2596813.9%
 
1775718.1%
 

D19_KONSUMTYP_MAX
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.598090258
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:01.241889image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q38
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.211879259
Coefficient of variation (CV)0.698524622
Kurtosis-1.722185233
Mean4.598090258
Median Absolute Deviation (MAD)2
Skewness0.3257588008
Sum196950
Variance10.31616837
MonotocityNot monotonic
2020-11-30T23:58:01.325403image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21436633.5%
 
8953522.3%
 
9752617.6%
 
1626514.6%
 
326256.1%
 
425165.9%
 
ValueCountFrequency (%) 
1626514.6%
 
21436633.5%
 
326256.1%
 
425165.9%
 
8953522.3%
 
9752617.6%
 
ValueCountFrequency (%) 
9752617.6%
 
8953522.3%
 
425165.9%
 
326256.1%
 
21436633.5%
 
1626514.6%
 

D19_KOSMETIK
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.147713212
Minimum0
Maximum7
Zeros28543
Zeros (%)66.6%
Memory size334.8 KiB
2020-11-30T23:58:01.416061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.054435537
Coefficient of variation (CV)1.422180355
Kurtosis-1.407166484
Mean2.147713212
Median Absolute Deviation (MAD)0
Skewness0.7413451557
Sum91993
Variance9.32957645
MonotocityNot monotonic
2020-11-30T23:58:01.495604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02854366.6%
 
6749417.5%
 
7663215.5%
 
3800.2%
 
5590.1%
 
412< 0.1%
 
29< 0.1%
 
14< 0.1%
 
ValueCountFrequency (%) 
02854366.6%
 
14< 0.1%
 
29< 0.1%
 
3800.2%
 
412< 0.1%
 
5590.1%
 
6749417.5%
 
7663215.5%
 
ValueCountFrequency (%) 
7663215.5%
 
6749417.5%
 
5590.1%
 
412< 0.1%
 
3800.2%
 
29< 0.1%
 
14< 0.1%
 
02854366.6%
 

D19_LEBENSMITTEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6944645484
Minimum0
Maximum7
Zeros37291
Zeros (%)87.1%
Memory size334.8 KiB
2020-11-30T23:58:01.581122image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.864956963
Coefficient of variation (CV)2.685460284
Kurtosis4.184987495
Mean0.6944645484
Median Absolute Deviation (MAD)0
Skewness2.437469637
Sum29746
Variance3.478064474
MonotocityNot monotonic
2020-11-30T23:58:01.666898image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03729187.1%
 
633137.7%
 
39952.3%
 
55531.3%
 
75491.3%
 
2830.2%
 
1290.1%
 
420< 0.1%
 
ValueCountFrequency (%) 
03729187.1%
 
1290.1%
 
2830.2%
 
39952.3%
 
420< 0.1%
 
55531.3%
 
633137.7%
 
75491.3%
 
ValueCountFrequency (%) 
75491.3%
 
633137.7%
 
55531.3%
 
420< 0.1%
 
39952.3%
 
2830.2%
 
1290.1%
 
03729187.1%
 

D19_LETZTER_KAUF_BRANCHE
Categorical

MISSING

Distinct35
Distinct (%)0.1%
Missing7526
Missing (%)17.6%
Memory size334.8 KiB
D19_UNBEKANNT
10115 
D19_SONSTIGE
2771 
D19_VERSICHERUNGEN
2576 
D19_VOLLSORTIMENT
2315 
D19_HAUS_DEKO
2216 
Other values (30)
15314 
ValueCountFrequency (%) 
D19_UNBEKANNT1011523.6%
 
D19_SONSTIGE27716.5%
 
D19_VERSICHERUNGEN25766.0%
 
D19_VOLLSORTIMENT23155.4%
 
D19_HAUS_DEKO22165.2%
 
D19_BUCH_CD21034.9%
 
D19_DROGERIEARTIKEL11012.6%
 
D19_SCHUHE10852.5%
 
D19_BEKLEIDUNG_GEH10732.5%
 
D19_BEKLEIDUNG_REST10142.4%
 
D19_ENERGIE9532.2%
 
D19_VERSAND_REST8822.1%
 
D19_BANKEN_DIREKT8221.9%
 
D19_LEBENSMITTEL8091.9%
 
D19_NAHRUNGSERGAENZUNG5831.4%
 
D19_TELKO_REST5341.2%
 
D19_TELKO_MOBILE5261.2%
 
D19_SAMMELARTIKEL4301.0%
 
D19_BANKEN_GROSS4221.0%
 
D19_TECHNIK4030.9%
 
D19_FREIZEIT3510.8%
 
D19_WEIN_FEINKOST2930.7%
 
D19_RATGEBER2780.6%
 
D19_KINDERARTIKEL2600.6%
 
D19_BANKEN_REST2360.6%
 
Other values (10)11562.7%
 
(Missing)752617.6%
 
2020-11-30T23:58:01.785577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters26
Unique unicode categories4 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
E5367610.2%
 
N524999.9%
 
_458678.7%
 
D451708.5%
 
1353076.7%
 
9353076.7%
 
T274885.2%
 
U214044.0%
 
K211354.0%
 
S206603.9%
 
R204673.9%
 
A188843.6%
 
I188053.6%
 
B176903.3%
 
n150522.8%
 
O137012.6%
 
G134402.5%
 
L124412.4%
 
H112572.1%
 
C82701.6%
 
a75261.4%
 
V59761.1%
 
M45440.9%
 
Z9340.2%
 
F6440.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter38951173.7%
 
Decimal Number7061413.4%
 
Connector Punctuation458678.7%
 
Lowercase Letter225784.3%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
E5367613.8%
 
N5249913.5%
 
D4517011.6%
 
T274887.1%
 
U214045.5%
 
K211355.4%
 
S206605.3%
 
R204675.3%
 
A188844.8%
 
I188054.8%
 
B176904.5%
 
O137013.5%
 
G134403.5%
 
L124413.2%
 
H112572.9%
 
C82702.1%
 
V59761.5%
 
M45441.2%
 
Z9340.2%
 
F6440.2%
 
W4260.1%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
13530750.0%
 
93530750.0%
 

Most frequent Connector Punctuation characters

ValueCountFrequency (%) 
_45867100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1505266.7%
 
a752633.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin41208978.0%
 
Common11648122.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
E5367613.0%
 
N5249912.7%
 
D4517011.0%
 
T274886.7%
 
U214045.2%
 
K211355.1%
 
S206605.0%
 
R204675.0%
 
A188844.6%
 
I188054.6%
 
B176904.3%
 
n150523.7%
 
O137013.3%
 
G134403.3%
 
L124413.0%
 
H112572.7%
 
C82702.0%
 
a75261.8%
 
V59761.5%
 
M45441.1%
 
Z9340.2%
 
F6440.2%
 
W4260.1%
 

Most frequent Common characters

ValueCountFrequency (%) 
_4586739.4%
 
13530730.3%
 
93530730.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII528570100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
E5367610.2%
 
N524999.9%
 
_458678.7%
 
D451708.5%
 
1353076.7%
 
9353076.7%
 
T274885.2%
 
U214044.0%
 
K211354.0%
 
S206603.9%
 
R204673.9%
 
A188843.6%
 
I188053.6%
 
B176903.3%
 
n150522.8%
 
O137012.6%
 
G134402.5%
 
L124412.4%
 
H112572.1%
 
C82701.6%
 
a75261.4%
 
V59761.1%
 
M45440.9%
 
Z9340.2%
 
F6440.1%
 

D19_LOTTO
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7526
Missing (%)17.6%
Infinite0
Infinite (%)0.0%
Mean2.931316736
Minimum0
Maximum7
Zeros20136
Zeros (%)47.0%
Memory size334.8 KiB
2020-11-30T23:58:01.881562image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.391546847
Coefficient of variation (CV)1.157004566
Kurtosis-1.888216768
Mean2.931316736
Median Absolute Deviation (MAD)0
Skewness0.3048574838
Sum103496
Variance11.50259002
MonotocityNot monotonic
2020-11-30T23:58:01.963427image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
02013647.0%
 
71281229.9%
 
621965.1%
 
3880.2%
 
5740.2%
 
21< 0.1%
 
(Missing)752617.6%
 
ValueCountFrequency (%) 
02013647.0%
 
21< 0.1%
 
3880.2%
 
5740.2%
 
621965.1%
 
71281229.9%
 
ValueCountFrequency (%) 
71281229.9%
 
621965.1%
 
5740.2%
 
3880.2%
 
21< 0.1%
 
02013647.0%
 

D19_NAHRUNGSERGAENZUNG
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5751406626
Minimum0
Maximum7
Zeros38321
Zeros (%)89.5%
Memory size334.8 KiB
2020-11-30T23:58:02.053442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.730934418
Coefficient of variation (CV)3.009584491
Kurtosis6.117875667
Mean0.5751406626
Median Absolute Deviation (MAD)0
Skewness2.801083794
Sum24635
Variance2.99613396
MonotocityNot monotonic
2020-11-30T23:58:02.136927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03832189.5%
 
625596.0%
 
36761.6%
 
76191.4%
 
55281.2%
 
2600.1%
 
1400.1%
 
4300.1%
 
ValueCountFrequency (%) 
03832189.5%
 
1400.1%
 
2600.1%
 
36761.6%
 
4300.1%
 
55281.2%
 
625596.0%
 
76191.4%
 
ValueCountFrequency (%) 
76191.4%
 
625596.0%
 
55281.2%
 
4300.1%
 
36761.6%
 
2600.1%
 
1400.1%
 
03832189.5%
 

D19_RATGEBER
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9255714052
Minimum0
Maximum7
Zeros35102
Zeros (%)82.0%
Memory size334.8 KiB
2020-11-30T23:58:02.226803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.0795642
Coefficient of variation (CV)2.246789592
Kurtosis1.996015082
Mean0.9255714052
Median Absolute Deviation (MAD)0
Skewness1.944204608
Sum39645
Variance4.324587263
MonotocityNot monotonic
2020-11-30T23:58:02.309390image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03510282.0%
 
6462110.8%
 
310432.4%
 
26381.5%
 
55951.4%
 
75221.2%
 
41910.4%
 
11210.3%
 
ValueCountFrequency (%) 
03510282.0%
 
11210.3%
 
26381.5%
 
310432.4%
 
41910.4%
 
55951.4%
 
6462110.8%
 
75221.2%
 
ValueCountFrequency (%) 
75221.2%
 
6462110.8%
 
55951.4%
 
41910.4%
 
310432.4%
 
26381.5%
 
11210.3%
 
03510282.0%
 

D19_REISEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.088599911
Minimum0
Maximum7
Zeros27986
Zeros (%)65.3%
Memory size334.8 KiB
2020-11-30T23:58:02.397540image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.927793259
Coefficient of variation (CV)1.401797081
Kurtosis-1.389809167
Mean2.088599911
Median Absolute Deviation (MAD)0
Skewness0.7360157479
Sum89461
Variance8.571973369
MonotocityNot monotonic
2020-11-30T23:58:02.475917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02798665.3%
 
6974122.7%
 
738308.9%
 
35021.2%
 
53530.8%
 
23360.8%
 
4590.1%
 
1260.1%
 
ValueCountFrequency (%) 
02798665.3%
 
1260.1%
 
23360.8%
 
35021.2%
 
4590.1%
 
53530.8%
 
6974122.7%
 
738308.9%
 
ValueCountFrequency (%) 
738308.9%
 
6974122.7%
 
53530.8%
 
4590.1%
 
35021.2%
 
23360.8%
 
1260.1%
 
02798665.3%
 

D19_SAMMELARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.507015619
Minimum0
Maximum7
Zeros31815
Zeros (%)74.3%
Memory size334.8 KiB
2020-11-30T23:58:02.561490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.591904934
Coefficient of variation (CV)1.719892549
Kurtosis-0.5697749271
Mean1.507015619
Median Absolute Deviation (MAD)0
Skewness1.172569631
Sum64550
Variance6.717971185
MonotocityNot monotonic
2020-11-30T23:58:02.642606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03181574.3%
 
6888420.7%
 
78982.1%
 
55991.4%
 
34971.2%
 
41010.2%
 
2310.1%
 
18< 0.1%
 
ValueCountFrequency (%) 
03181574.3%
 
18< 0.1%
 
2310.1%
 
34971.2%
 
41010.2%
 
55991.4%
 
6888420.7%
 
78982.1%
 
ValueCountFrequency (%) 
78982.1%
 
6888420.7%
 
55991.4%
 
41010.2%
 
34971.2%
 
2310.1%
 
18< 0.1%
 
03181574.3%
 

D19_SCHUHE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5482688581
Minimum0
Maximum7
Zeros37362
Zeros (%)87.2%
Memory size334.8 KiB
2020-11-30T23:58:02.730513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.549446909
Coefficient of variation (CV)2.826071345
Kurtosis6.478267348
Mean0.5482688581
Median Absolute Deviation (MAD)0
Skewness2.789395378
Sum23484
Variance2.400785724
MonotocityNot monotonic
2020-11-30T23:58:02.814754image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03736287.2%
 
617974.2%
 
317734.1%
 
58612.0%
 
25501.3%
 
71890.4%
 
11830.4%
 
41180.3%
 
ValueCountFrequency (%) 
03736287.2%
 
11830.4%
 
25501.3%
 
317734.1%
 
41180.3%
 
58612.0%
 
617974.2%
 
71890.4%
 
ValueCountFrequency (%) 
71890.4%
 
617974.2%
 
58612.0%
 
41180.3%
 
317734.1%
 
25501.3%
 
11830.4%
 
03736287.2%
 

D19_SONSTIGE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.636448533
Minimum0
Maximum7
Zeros15027
Zeros (%)35.1%
Memory size334.8 KiB
2020-11-30T23:58:02.902476image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.885462871
Coefficient of variation (CV)0.7934837644
Kurtosis-1.712807246
Mean3.636448533
Median Absolute Deviation (MAD)2
Skewness-0.3078013295
Sum155760
Variance8.325895978
MonotocityNot monotonic
2020-11-30T23:58:02.985549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
61622837.9%
 
01502735.1%
 
7515912.0%
 
330227.1%
 
519224.5%
 
26671.6%
 
44871.1%
 
13210.7%
 
ValueCountFrequency (%) 
01502735.1%
 
13210.7%
 
26671.6%
 
330227.1%
 
44871.1%
 
519224.5%
 
61622837.9%
 
7515912.0%
 
ValueCountFrequency (%) 
7515912.0%
 
61622837.9%
 
519224.5%
 
44871.1%
 
330227.1%
 
26671.6%
 
13210.7%
 
01502735.1%
 

D19_SOZIALES
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7526
Missing (%)17.6%
Infinite0
Infinite (%)0.0%
Mean1.694451525
Minimum0
Maximum5
Zeros9585
Zeros (%)22.4%
Memory size334.8 KiB
2020-11-30T23:58:03.072586image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.50872895
Coefficient of variation (CV)0.8903936923
Kurtosis-0.9846823089
Mean1.694451525
Median Absolute Deviation (MAD)1
Skewness0.494906352
Sum59826
Variance2.276263045
MonotocityNot monotonic
2020-11-30T23:58:03.159837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11097825.6%
 
0958522.4%
 
3871420.3%
 
431547.4%
 
514463.4%
 
214303.3%
 
(Missing)752617.6%
 
ValueCountFrequency (%) 
0958522.4%
 
11097825.6%
 
214303.3%
 
3871420.3%
 
431547.4%
 
514463.4%
 
ValueCountFrequency (%) 
514463.4%
 
431547.4%
 
3871420.3%
 
214303.3%
 
11097825.6%
 
0958522.4%
 

D19_TECHNIK
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.445661056
Minimum0
Maximum7
Zeros25431
Zeros (%)59.4%
Memory size334.8 KiB
2020-11-30T23:58:03.240706image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.014842254
Coefficient of variation (CV)1.232731023
Kurtosis-1.699553738
Mean2.445661056
Median Absolute Deviation (MAD)0
Skewness0.4726402389
Sum104755
Variance9.089273816
MonotocityNot monotonic
2020-11-30T23:58:03.320029image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02543159.4%
 
61108925.9%
 
7437910.2%
 
38952.1%
 
58822.1%
 
4870.2%
 
2550.1%
 
115< 0.1%
 
ValueCountFrequency (%) 
02543159.4%
 
115< 0.1%
 
2550.1%
 
38952.1%
 
4870.2%
 
58822.1%
 
61108925.9%
 
7437910.2%
 
ValueCountFrequency (%) 
7437910.2%
 
61108925.9%
 
58822.1%
 
4870.2%
 
38952.1%
 
2550.1%
 
115< 0.1%
 
02543159.4%
 

D19_TELKO_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.05084864474
Minimum0
Maximum6
Zeros41050
Zeros (%)95.8%
Memory size334.8 KiB
2020-11-30T23:58:03.405650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.2668163611
Coefficient of variation (CV)5.247265931
Kurtosis63.51330714
Mean0.05084864474
Median Absolute Deviation (MAD)0
Skewness6.766888931
Sum2178
Variance0.07119097058
MonotocityNot monotonic
2020-11-30T23:58:03.486533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
04105095.8%
 
114503.4%
 
22950.7%
 
3220.1%
 
410< 0.1%
 
54< 0.1%
 
62< 0.1%
 
ValueCountFrequency (%) 
04105095.8%
 
114503.4%
 
22950.7%
 
3220.1%
 
410< 0.1%
 
54< 0.1%
 
62< 0.1%
 
ValueCountFrequency (%) 
62< 0.1%
 
54< 0.1%
 
410< 0.1%
 
3220.1%
 
22950.7%
 
114503.4%
 
04105095.8%
 

D19_TELKO_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09396960288
Minimum0
Maximum6
Zeros39657
Zeros (%)92.6%
Memory size334.8 KiB
2020-11-30T23:58:03.573382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3645673165
Coefficient of variation (CV)3.879630278
Kurtosis31.64969978
Mean0.09396960288
Median Absolute Deviation (MAD)0
Skewness4.846820483
Sum4025
Variance0.1329093283
MonotocityNot monotonic
2020-11-30T23:58:03.655846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03965792.6%
 
124455.7%
 
26491.5%
 
3600.1%
 
414< 0.1%
 
66< 0.1%
 
52< 0.1%
 
ValueCountFrequency (%) 
03965792.6%
 
124455.7%
 
26491.5%
 
3600.1%
 
414< 0.1%
 
52< 0.1%
 
66< 0.1%
 
ValueCountFrequency (%) 
66< 0.1%
 
52< 0.1%
 
414< 0.1%
 
3600.1%
 
26491.5%
 
124455.7%
 
03965792.6%
 

D19_TELKO_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.469777975
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:03.747123image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.320907488
Coefficient of variation (CV)0.1394866375
Kurtosis11.09863814
Mean9.469777975
Median Absolute Deviation (MAD)0
Skewness-3.20240784
Sum405619
Variance1.744796591
MonotocityNot monotonic
2020-11-30T23:58:03.832889image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103339878.0%
 
9463110.8%
 
816283.8%
 
513103.1%
 
77441.7%
 
66491.5%
 
41850.4%
 
11150.3%
 
2900.2%
 
3830.2%
 
ValueCountFrequency (%) 
11150.3%
 
2900.2%
 
3830.2%
 
41850.4%
 
513103.1%
 
66491.5%
 
77441.7%
 
816283.8%
 
9463110.8%
 
103339878.0%
 
ValueCountFrequency (%) 
103339878.0%
 
9463110.8%
 
816283.8%
 
77441.7%
 
66491.5%
 
513103.1%
 
41850.4%
 
3830.2%
 
2900.2%
 
11150.3%
 

D19_TELKO_MOBILE
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8659444821
Minimum0
Maximum7
Zeros35991
Zeros (%)84.0%
Memory size334.8 KiB
2020-11-30T23:58:03.929913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.047166635
Coefficient of variation (CV)2.364085317
Kurtosis2.300497666
Mean0.8659444821
Median Absolute Deviation (MAD)0
Skewness2.034681183
Sum37091
Variance4.190891231
MonotocityNot monotonic
2020-11-30T23:58:04.032155image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03599184.0%
 
6464510.8%
 
39432.2%
 
56091.4%
 
73750.9%
 
41150.3%
 
21070.2%
 
1480.1%
 
ValueCountFrequency (%) 
03599184.0%
 
1480.1%
 
21070.2%
 
39432.2%
 
41150.3%
 
56091.4%
 
6464510.8%
 
73750.9%
 
ValueCountFrequency (%) 
73750.9%
 
6464510.8%
 
56091.4%
 
41150.3%
 
39432.2%
 
21070.2%
 
1480.1%
 
03599184.0%
 

D19_TELKO_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.777391264
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:04.132838image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9015098791
Coefficient of variation (CV)0.09220351879
Kurtosis27.69763449
Mean9.777391264
Median Absolute Deviation (MAD)0
Skewness-5.042918246
Sum418795
Variance0.8127200621
MonotocityNot monotonic
2020-11-30T23:58:04.223976image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103904291.1%
 
917614.1%
 
58201.9%
 
87231.7%
 
62050.5%
 
71510.4%
 
4460.1%
 
3310.1%
 
1300.1%
 
2240.1%
 
ValueCountFrequency (%) 
1300.1%
 
2240.1%
 
3310.1%
 
4460.1%
 
58201.9%
 
62050.5%
 
71510.4%
 
87231.7%
 
917614.1%
 
103904291.1%
 
ValueCountFrequency (%) 
103904291.1%
 
917614.1%
 
87231.7%
 
71510.4%
 
62050.5%
 
58201.9%
 
4460.1%
 
3310.1%
 
2240.1%
 
1300.1%
 

D19_TELKO_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.977657414
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:04.312492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.262598957
Coefficient of variation (CV)0.02631869848
Kurtosis348.3448034
Mean9.977657414
Median Absolute Deviation (MAD)0
Skewness-16.72881458
Sum427373
Variance0.0689582122
MonotocityNot monotonic
2020-11-30T23:58:04.394533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
104235398.9%
 
92600.6%
 
81100.3%
 
7370.1%
 
5310.1%
 
6280.1%
 
46< 0.1%
 
34< 0.1%
 
13< 0.1%
 
21< 0.1%
 
ValueCountFrequency (%) 
13< 0.1%
 
21< 0.1%
 
34< 0.1%
 
46< 0.1%
 
5310.1%
 
6280.1%
 
7370.1%
 
81100.3%
 
92600.6%
 
104235398.9%
 
ValueCountFrequency (%) 
104235398.9%
 
92600.6%
 
81100.3%
 
7370.1%
 
6280.1%
 
5310.1%
 
46< 0.1%
 
34< 0.1%
 
21< 0.1%
 
13< 0.1%
 

D19_TELKO_ONLINE_QUOTE_12
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7526
Missing (%)17.6%
Memory size334.8 KiB
0
35262 
10
 
43
5
 
2
ValueCountFrequency (%) 
03526282.3%
 
10430.1%
 
52< 0.1%
 
(Missing)752617.6%
 
2020-11-30T23:58:04.497381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
07061254.9%
 
.3530727.5%
 
n1505211.7%
 
a75265.9%
 
143< 0.1%
 
52< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7065755.0%
 
Other Punctuation3530727.5%
 
Lowercase Letter2257817.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
07061299.9%
 
1430.1%
 
52< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35307100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1505266.7%
 
a752633.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10596482.4%
 
Latin2257817.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
07061266.6%
 
.3530733.3%
 
143< 0.1%
 
52< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1505266.7%
 
a752633.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128542100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
07061254.9%
 
.3530727.5%
 
n1505211.7%
 
a75265.9%
 
143< 0.1%
 
52< 0.1%
 

D19_TELKO_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.627226671
Minimum0
Maximum7
Zeros37808
Zeros (%)88.3%
Memory size334.8 KiB
2020-11-30T23:58:04.586301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.76954194
Coefficient of variation (CV)2.821216031
Kurtosis4.852339672
Mean0.627226671
Median Absolute Deviation (MAD)0
Skewness2.574687489
Sum26866
Variance3.131278676
MonotocityNot monotonic
2020-11-30T23:58:04.668163image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03780888.3%
 
631547.4%
 
37691.8%
 
57151.7%
 
72210.5%
 
4990.2%
 
2500.1%
 
117< 0.1%
 
ValueCountFrequency (%) 
03780888.3%
 
117< 0.1%
 
2500.1%
 
37691.8%
 
4990.2%
 
57151.7%
 
631547.4%
 
72210.5%
 
ValueCountFrequency (%) 
72210.5%
 
631547.4%
 
57151.7%
 
4990.2%
 
37691.8%
 
2500.1%
 
117< 0.1%
 
03780888.3%
 

D19_TIERARTIKEL
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2721733243
Minimum0
Maximum7
Zeros40738
Zeros (%)95.1%
Memory size334.8 KiB
2020-11-30T23:58:04.756227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.243032537
Coefficient of variation (CV)4.567062332
Kurtosis19.40693982
Mean0.2721733243
Median Absolute Deviation (MAD)0
Skewness4.555122358
Sum11658
Variance1.545129889
MonotocityNot monotonic
2020-11-30T23:58:04.857869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
04073895.1%
 
68291.9%
 
76191.4%
 
33720.9%
 
52050.5%
 
4360.1%
 
2320.1%
 
12< 0.1%
 
ValueCountFrequency (%) 
04073895.1%
 
12< 0.1%
 
2320.1%
 
33720.9%
 
4360.1%
 
52050.5%
 
68291.9%
 
76191.4%
 
ValueCountFrequency (%) 
76191.4%
 
68291.9%
 
52050.5%
 
4360.1%
 
33720.9%
 
2320.1%
 
12< 0.1%
 
04073895.1%
 

D19_VERSAND_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7832512315
Minimum0
Maximum6
Zeros27471
Zeros (%)64.1%
Memory size334.8 KiB
2020-11-30T23:58:04.949250image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.291907736
Coefficient of variation (CV)1.649416795
Kurtosis2.37141977
Mean0.7832512315
Median Absolute Deviation (MAD)0
Skewness1.746948255
Sum33549
Variance1.669025598
MonotocityNot monotonic
2020-11-30T23:58:05.027018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02747164.1%
 
1587513.7%
 
2471111.0%
 
319724.6%
 
418614.3%
 
57661.8%
 
61770.4%
 
ValueCountFrequency (%) 
02747164.1%
 
1587513.7%
 
2471111.0%
 
319724.6%
 
418614.3%
 
57661.8%
 
61770.4%
 
ValueCountFrequency (%) 
61770.4%
 
57661.8%
 
418614.3%
 
319724.6%
 
2471111.0%
 
1587513.7%
 
02747164.1%
 

D19_VERSAND_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.206476315
Minimum0
Maximum6
Zeros23150
Zeros (%)54.0%
Memory size334.8 KiB
2020-11-30T23:58:05.109589image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q32
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.652162099
Coefficient of variation (CV)1.369411135
Kurtosis0.4834056438
Mean1.206476315
Median Absolute Deviation (MAD)0
Skewness1.253738207
Sum51677
Variance2.729639603
MonotocityNot monotonic
2020-11-30T23:58:05.183644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
02315054.0%
 
1561113.1%
 
2556013.0%
 
431077.3%
 
326926.3%
 
518364.3%
 
68772.0%
 
ValueCountFrequency (%) 
02315054.0%
 
1561113.1%
 
2556013.0%
 
326926.3%
 
431077.3%
 
518364.3%
 
68772.0%
 
ValueCountFrequency (%) 
68772.0%
 
518364.3%
 
431077.3%
 
326926.3%
 
2556013.0%
 
1561113.1%
 
02315054.0%
 

D19_VERSAND_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.142226788
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:05.268003image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q15
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.034255131
Coefficient of variation (CV)0.4248332098
Kurtosis-0.8807083176
Mean7.142226788
Median Absolute Deviation (MAD)1
Skewness-0.7097194669
Sum305923
Variance9.206704203
MonotocityNot monotonic
2020-11-30T23:58:05.351628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101467034.2%
 
9690316.1%
 
5522512.2%
 
829506.9%
 
128756.7%
 
225485.9%
 
621575.0%
 
719904.6%
 
419834.6%
 
315323.6%
 
ValueCountFrequency (%) 
128756.7%
 
225485.9%
 
315323.6%
 
419834.6%
 
5522512.2%
 
621575.0%
 
719904.6%
 
829506.9%
 
9690316.1%
 
101467034.2%
 
ValueCountFrequency (%) 
101467034.2%
 
9690316.1%
 
829506.9%
 
719904.6%
 
621575.0%
 
5522512.2%
 
419834.6%
 
315323.6%
 
225485.9%
 
128756.7%
 

D19_VERSAND_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.448205823
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:05.441979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q18
median9
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.174877704
Coefficient of variation (CV)0.257436638
Kurtosis1.869063678
Mean8.448205823
Median Absolute Deviation (MAD)1
Skewness-1.611856604
Sum361862
Variance4.730093029
MonotocityNot monotonic
2020-11-30T23:58:05.529701image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
101973246.1%
 
9964822.5%
 
839359.2%
 
534198.0%
 
718774.4%
 
615353.6%
 
28672.0%
 
47441.7%
 
15761.3%
 
35001.2%
 
ValueCountFrequency (%) 
15761.3%
 
28672.0%
 
35001.2%
 
47441.7%
 
534198.0%
 
615353.6%
 
718774.4%
 
839359.2%
 
9964822.5%
 
101973246.1%
 
ValueCountFrequency (%) 
101973246.1%
 
9964822.5%
 
839359.2%
 
718774.4%
 
615353.6%
 
534198.0%
 
47441.7%
 
35001.2%
 
28672.0%
 
15761.3%
 

D19_VERSAND_ONLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.822566713
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:05.619329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q16
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.935505166
Coefficient of variation (CV)0.3752611226
Kurtosis-0.1980577297
Mean7.822566713
Median Absolute Deviation (MAD)0
Skewness-1.099342817
Sum335064
Variance8.617190582
MonotocityNot monotonic
2020-11-30T23:58:05.696405image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
102172650.7%
 
9504711.8%
 
537208.7%
 
123155.4%
 
820134.7%
 
218684.4%
 
617924.2%
 
415783.7%
 
715603.6%
 
312142.8%
 
ValueCountFrequency (%) 
123155.4%
 
218684.4%
 
312142.8%
 
415783.7%
 
537208.7%
 
617924.2%
 
715603.6%
 
820134.7%
 
9504711.8%
 
102172650.7%
 
ValueCountFrequency (%) 
102172650.7%
 
9504711.8%
 
820134.7%
 
715603.6%
 
617924.2%
 
537208.7%
 
415783.7%
 
312142.8%
 
218684.4%
 
123155.4%
 

D19_VERSAND_ONLINE_QUOTE_12
Real number (ℝ≥0)

MISSING
ZEROS

Distinct11
Distinct (%)< 0.1%
Missing7526
Missing (%)17.6%
Infinite0
Infinite (%)0.0%
Mean2.651343926
Minimum0
Maximum10
Zeros24464
Zeros (%)57.1%
Memory size334.8 KiB
2020-11-30T23:58:05.778517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.204105631
Coefficient of variation (CV)1.585650805
Kurtosis-0.7851734137
Mean2.651343926
Median Absolute Deviation (MAD)0
Skewness1.052326314
Sum93611
Variance17.67450416
MonotocityNot monotonic
2020-11-30T23:58:05.865354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
02446457.1%
 
10759017.7%
 
58842.1%
 
74971.2%
 
84921.1%
 
34501.1%
 
92800.7%
 
21950.5%
 
11680.4%
 
61500.4%
 
41370.3%
 
(Missing)752617.6%
 
ValueCountFrequency (%) 
02446457.1%
 
11680.4%
 
21950.5%
 
34501.1%
 
41370.3%
 
58842.1%
 
61500.4%
 
74971.2%
 
84921.1%
 
92800.7%
 
ValueCountFrequency (%) 
10759017.7%
 
92800.7%
 
84921.1%
 
74971.2%
 
61500.4%
 
58842.1%
 
41370.3%
 
34501.1%
 
21950.5%
 
11680.4%
 

D19_VERSAND_REST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7377255854
Minimum0
Maximum7
Zeros36177
Zeros (%)84.5%
Memory size334.8 KiB
2020-11-30T23:58:05.949388image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.820275092
Coefficient of variation (CV)2.467414887
Kurtosis3.49764506
Mean0.7377255854
Median Absolute Deviation (MAD)0
Skewness2.262244117
Sum31599
Variance3.313401411
MonotocityNot monotonic
2020-11-30T23:58:06.031220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03617784.5%
 
630397.1%
 
318744.4%
 
510172.4%
 
22430.6%
 
72020.5%
 
41590.4%
 
11220.3%
 
ValueCountFrequency (%) 
03617784.5%
 
11220.3%
 
22430.6%
 
318744.4%
 
41590.4%
 
510172.4%
 
630397.1%
 
72020.5%
 
ValueCountFrequency (%) 
72020.5%
 
630397.1%
 
510172.4%
 
41590.4%
 
318744.4%
 
22430.6%
 
11220.3%
 
03617784.5%
 

D19_VERSI_ANZ_12
Real number (ℝ≥0)

ZEROS

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1083043448
Minimum0
Maximum5
Zeros39452
Zeros (%)92.1%
Memory size334.8 KiB
2020-11-30T23:58:06.117747image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4104131181
Coefficient of variation (CV)3.789442787
Kurtosis24.72175975
Mean0.1083043448
Median Absolute Deviation (MAD)0
Skewness4.568492051
Sum4639
Variance0.1684389275
MonotocityNot monotonic
2020-11-30T23:58:06.204607image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
03945292.1%
 
123475.5%
 
28632.0%
 
31220.3%
 
4450.1%
 
54< 0.1%
 
ValueCountFrequency (%) 
03945292.1%
 
123475.5%
 
28632.0%
 
31220.3%
 
4450.1%
 
54< 0.1%
 
ValueCountFrequency (%) 
54< 0.1%
 
4450.1%
 
31220.3%
 
28632.0%
 
123475.5%
 
03945292.1%
 

D19_VERSI_ANZ_24
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1922583055
Minimum0
Maximum6
Zeros37442
Zeros (%)87.4%
Memory size334.8 KiB
2020-11-30T23:58:06.288535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum6
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.5757389734
Coefficient of variation (CV)2.994611712
Kurtosis14.97368466
Mean0.1922583055
Median Absolute Deviation (MAD)0
Skewness3.605622239
Sum8235
Variance0.3314753655
MonotocityNot monotonic
2020-11-30T23:58:06.368007image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
03744287.4%
 
132527.6%
 
216323.8%
 
33320.8%
 
41550.4%
 
517< 0.1%
 
63< 0.1%
 
ValueCountFrequency (%) 
03744287.4%
 
132527.6%
 
216323.8%
 
33320.8%
 
41550.4%
 
517< 0.1%
 
63< 0.1%
 
ValueCountFrequency (%) 
63< 0.1%
 
517< 0.1%
 
41550.4%
 
33320.8%
 
216323.8%
 
132527.6%
 
03744287.4%
 

D19_VERSI_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.165549926
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:06.456877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.889091213
Coefficient of variation (CV)0.2061077871
Kurtosis6.187817885
Mean9.165549926
Median Absolute Deviation (MAD)0
Skewness-2.593980584
Sum392588
Variance3.568665611
MonotocityNot monotonic
2020-11-30T23:58:06.536544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
103213975.0%
 
936818.6%
 
816223.8%
 
515633.6%
 
611302.6%
 
78802.1%
 
27341.7%
 
44101.0%
 
13960.9%
 
32780.6%
 
ValueCountFrequency (%) 
13960.9%
 
27341.7%
 
32780.6%
 
44101.0%
 
515633.6%
 
611302.6%
 
78802.1%
 
816223.8%
 
936818.6%
 
103213975.0%
 
ValueCountFrequency (%) 
103213975.0%
 
936818.6%
 
816223.8%
 
78802.1%
 
611302.6%
 
515633.6%
 
44101.0%
 
32780.6%
 
27341.7%
 
13960.9%
 

D19_VERSI_OFFLINE_DATUM
Real number (ℝ≥0)

Distinct10
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.904326104
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:06.621481image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.6159444532
Coefficient of variation (CV)0.06218943588
Kurtosis61.57562723
Mean9.904326104
Median Absolute Deviation (MAD)0
Skewness-7.581331459
Sum424232
Variance0.3793875694
MonotocityNot monotonic
2020-11-30T23:58:06.704529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
104138396.6%
 
95691.3%
 
54551.1%
 
82520.6%
 
6870.2%
 
7550.1%
 
411< 0.1%
 
19< 0.1%
 
36< 0.1%
 
26< 0.1%
 
ValueCountFrequency (%) 
19< 0.1%
 
26< 0.1%
 
36< 0.1%
 
411< 0.1%
 
54551.1%
 
6870.2%
 
7550.1%
 
82520.6%
 
95691.3%
 
104138396.6%
 
ValueCountFrequency (%) 
104138396.6%
 
95691.3%
 
82520.6%
 
7550.1%
 
6870.2%
 
54551.1%
 
411< 0.1%
 
36< 0.1%
 
26< 0.1%
 
19< 0.1%
 

D19_VERSI_ONLINE_DATUM
Real number (ℝ≥0)

SKEWED

Distinct9
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.985245021
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:06.799678image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q110
median10
Q310
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.240658245
Coefficient of variation (CV)0.02410138604
Kurtosis500.3226795
Mean9.985245021
Median Absolute Deviation (MAD)0
Skewness-20.76506053
Sum427698
Variance0.05791639086
MonotocityNot monotonic
2020-11-30T23:58:06.885910image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
104259899.5%
 
9850.2%
 
8510.1%
 
5320.1%
 
7300.1%
 
6220.1%
 
38< 0.1%
 
44< 0.1%
 
13< 0.1%
 
ValueCountFrequency (%) 
13< 0.1%
 
38< 0.1%
 
44< 0.1%
 
5320.1%
 
6220.1%
 
7300.1%
 
8510.1%
 
9850.2%
 
104259899.5%
 
ValueCountFrequency (%) 
104259899.5%
 
9850.2%
 
8510.1%
 
7300.1%
 
6220.1%
 
5320.1%
 
44< 0.1%
 
38< 0.1%
 
13< 0.1%
 

D19_VERSI_ONLINE_QUOTE_12
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7526
Missing (%)17.6%
Memory size334.8 KiB
0
35260 
10
 
43
5
 
4
ValueCountFrequency (%) 
03526082.3%
 
10430.1%
 
54< 0.1%
 
(Missing)752617.6%
 
2020-11-30T23:58:06.993442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
07061054.9%
 
.3530727.5%
 
n1505211.7%
 
a75265.9%
 
143< 0.1%
 
54< 0.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7065755.0%
 
Other Punctuation3530727.5%
 
Lowercase Letter2257817.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
07061099.9%
 
1430.1%
 
54< 0.1%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35307100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1505266.7%
 
a752633.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10596482.4%
 
Latin2257817.6%
 

Most frequent Common characters

ValueCountFrequency (%) 
07061066.6%
 
.3530733.3%
 
143< 0.1%
 
54< 0.1%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1505266.7%
 
a752633.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128542100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
07061054.9%
 
.3530727.5%
 
n1505211.7%
 
a75265.9%
 
143< 0.1%
 
54< 0.1%
 

D19_VERSICHERUNGEN
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.207666986
Minimum0
Maximum7
Zeros31891
Zeros (%)74.5%
Memory size334.8 KiB
2020-11-30T23:58:07.084248image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.212312528
Coefficient of variation (CV)1.831889548
Kurtosis0.4104389677
Mean1.207666986
Median Absolute Deviation (MAD)0
Skewness1.466233359
Sum51728
Variance4.894326722
MonotocityNot monotonic
2020-11-30T23:58:07.165674image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03189174.5%
 
6530312.4%
 
323475.5%
 
514253.3%
 
26341.5%
 
45851.4%
 
14000.9%
 
72480.6%
 
ValueCountFrequency (%) 
03189174.5%
 
14000.9%
 
26341.5%
 
323475.5%
 
45851.4%
 
514253.3%
 
6530312.4%
 
72480.6%
 
ValueCountFrequency (%) 
72480.6%
 
6530312.4%
 
514253.3%
 
45851.4%
 
323475.5%
 
26341.5%
 
14000.9%
 
03189174.5%
 

D19_VOLLSORTIMENT
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.907314454
Minimum0
Maximum7
Zeros20117
Zeros (%)47.0%
Memory size334.8 KiB
2020-11-30T23:58:07.252215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median3
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)6

Descriptive statistics

Standard deviation2.895951369
Coefficient of variation (CV)0.9960915527
Kurtosis-1.842331755
Mean2.907314454
Median Absolute Deviation (MAD)3
Skewness0.1132148007
Sum124529
Variance8.386534329
MonotocityNot monotonic
2020-11-30T23:58:07.335054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
02011747.0%
 
61457234.0%
 
330207.1%
 
724245.7%
 
517714.1%
 
24601.1%
 
42750.6%
 
11940.5%
 
ValueCountFrequency (%) 
02011747.0%
 
11940.5%
 
24601.1%
 
330207.1%
 
42750.6%
 
517714.1%
 
61457234.0%
 
724245.7%
 
ValueCountFrequency (%) 
724245.7%
 
61457234.0%
 
517714.1%
 
42750.6%
 
330207.1%
 
24601.1%
 
11940.5%
 
02011747.0%
 

D19_WEIN_FEINKOST
Real number (ℝ≥0)

ZEROS

Distinct8
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8780613079
Minimum0
Maximum7
Zeros36598
Zeros (%)85.4%
Memory size334.8 KiB
2020-11-30T23:58:07.423943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6
Maximum7
Range7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.164692062
Coefficient of variation (CV)2.465308563
Kurtosis2.638232302
Mean0.8780613079
Median Absolute Deviation (MAD)0
Skewness2.123174833
Sum37610
Variance4.685891721
MonotocityNot monotonic
2020-11-30T23:58:07.505864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
03659885.4%
 
633107.7%
 
720504.8%
 
34411.0%
 
53860.9%
 
4260.1%
 
221< 0.1%
 
11< 0.1%
 
ValueCountFrequency (%) 
03659885.4%
 
11< 0.1%
 
221< 0.1%
 
34411.0%
 
4260.1%
 
53860.9%
 
633107.7%
 
720504.8%
 
ValueCountFrequency (%) 
720504.8%
 
633107.7%
 
53860.9%
 
4260.1%
 
34411.0%
 
221< 0.1%
 
11< 0.1%
 
03659885.4%
 

DSL_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Memory size334.8 KiB
1
34547 
0
 
659
(Missing)
7627 
ValueCountFrequency (%) 
13454780.7%
 
06591.5%
 
(Missing)762717.8%
 

EINGEFUEGT_AM
Categorical

HIGH CARDINALITY
MISSING

Distinct1608
Distinct (%)4.6%
Missing7627
Missing (%)17.8%
Memory size334.8 KiB
1992-02-10 00:00:00
18096 
1992-02-12 00:00:00
8141 
1995-02-07 00:00:00
 
511
1993-03-01 00:00:00
 
239
2003-11-18 00:00:00
 
223
Other values (1603)
7996 
ValueCountFrequency (%) 
1992-02-10 00:00:001809642.2%
 
1992-02-12 00:00:00814119.0%
 
1995-02-07 00:00:005111.2%
 
1993-03-01 00:00:002390.6%
 
2003-11-18 00:00:002230.5%
 
2005-12-16 00:00:001530.4%
 
1994-02-03 00:00:001100.3%
 
1995-10-17 00:00:00880.2%
 
1993-09-22 00:00:00860.2%
 
2004-04-14 00:00:00790.2%
 
1993-09-21 00:00:00790.2%
 
1994-12-13 00:00:00660.2%
 
2005-08-23 00:00:00650.2%
 
2000-05-10 00:00:00630.1%
 
2005-04-15 00:00:00580.1%
 
1995-10-10 00:00:00560.1%
 
1992-02-21 00:00:00520.1%
 
1996-03-07 00:00:00520.1%
 
1993-10-21 00:00:00500.1%
 
1993-03-23 00:00:00460.1%
 
1993-09-16 00:00:00450.1%
 
1993-04-01 00:00:00450.1%
 
1993-11-03 00:00:00440.1%
 
1994-05-19 00:00:00440.1%
 
1996-01-26 00:00:00430.1%
 
Other values (1583)667215.6%
 
(Missing)762717.8%
 
2020-11-30T23:58:07.639233image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique688 ?
Unique (%)2.0%

Overview of Unicode Properties

Unique unicode characters15
Unique unicode categories5 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
027071739.1%
 
-7041210.2%
 
:7041210.2%
 
2685169.9%
 
9682089.9%
 
1672969.7%
 
352065.1%
 
n152542.2%
 
a76271.1%
 
339320.6%
 
535000.5%
 
431580.5%
 
729470.4%
 
627090.4%
 
819010.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number49288471.2%
 
Dash Punctuation7041210.2%
 
Other Punctuation7041210.2%
 
Space Separator352065.1%
 
Lowercase Letter228813.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
027071754.9%
 
26851613.9%
 
96820813.8%
 
16729613.7%
 
339320.8%
 
535000.7%
 
431580.6%
 
729470.6%
 
627090.5%
 
819010.4%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-70412100.0%
 

Most frequent Space Separator characters

ValueCountFrequency (%) 
35206100.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
:70412100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1525466.7%
 
a762733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common66891496.7%
 
Latin228813.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
027071740.5%
 
-7041210.5%
 
:7041210.5%
 
26851610.2%
 
96820810.2%
 
16729610.1%
 
352065.3%
 
339320.6%
 
535000.5%
 
431580.5%
 
729470.4%
 
627090.4%
 
819010.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1525466.7%
 
a762733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII691795100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
027071739.1%
 
-7041210.2%
 
:7041210.2%
 
2685169.9%
 
9682089.9%
 
1672969.7%
 
352065.1%
 
n152542.2%
 
a76271.1%
 
339320.6%
 
535000.5%
 
431580.5%
 
729470.4%
 
627090.4%
 
819010.3%
 

EINGEZOGENAM_HH_JAHR
Real number (ℝ≥0)

MISSING

Distinct32
Distinct (%)0.1%
Missing6889
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean1998.871689
Minimum1987
Maximum2018
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:07.758948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1987
5-th percentile1994
Q11994
median1997
Q32002
95-th percentile2011
Maximum2018
Range31
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.79569972
Coefficient of variation (CV)0.00289948562
Kurtosis0.2556956316
Mean1998.871689
Median Absolute Deviation (MAD)3
Skewness1.09852715
Sum71847444
Variance33.59013524
MonotocityNot monotonic
2020-11-30T23:58:07.860453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%) 
19941445833.8%
 
1997510911.9%
 
200421054.9%
 
199813263.1%
 
200113083.1%
 
200012663.0%
 
199912292.9%
 
200212052.8%
 
200710842.5%
 
20087821.8%
 
20036831.6%
 
20056681.6%
 
20065391.3%
 
20155151.2%
 
19965121.2%
 
20094861.1%
 
20124281.0%
 
20114060.9%
 
20144020.9%
 
19953960.9%
 
20133780.9%
 
20103760.9%
 
1993950.2%
 
1992600.1%
 
1991330.1%
 
Other values (7)950.2%
 
(Missing)688916.1%
 
ValueCountFrequency (%) 
19873< 0.1%
 
19887< 0.1%
 
198915< 0.1%
 
1990240.1%
 
1991330.1%
 
1992600.1%
 
1993950.2%
 
19941445833.8%
 
19953960.9%
 
19965121.2%
 
ValueCountFrequency (%) 
2018220.1%
 
201710< 0.1%
 
201614< 0.1%
 
20155151.2%
 
20144020.9%
 
20133780.9%
 
20124281.0%
 
20114060.9%
 
20103760.9%
 
20094861.1%
 

EWDICHTE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7641
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean3.757899523
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:07.955877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.740302366
Coefficient of variation (CV)0.4631050818
Kurtosis-1.34466679
Mean3.757899523
Median Absolute Deviation (MAD)2
Skewness-0.1707442069
Sum132248
Variance3.028652324
MonotocityNot monotonic
2020-11-30T23:58:08.042625image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
6772718.0%
 
2683816.0%
 
5674415.7%
 
4570713.3%
 
1443310.3%
 
337438.7%
 
(Missing)764117.8%
 
ValueCountFrequency (%) 
1443310.3%
 
2683816.0%
 
337438.7%
 
4570713.3%
 
5674415.7%
 
6772718.0%
 
ValueCountFrequency (%) 
6772718.0%
 
5674415.7%
 
4570713.3%
 
337438.7%
 
2683816.0%
 
1443310.3%
 

EXTSEL992
Real number (ℝ≥0)

MISSING

Distinct56
Distinct (%)0.2%
Missing15809
Missing (%)36.9%
Infinite0
Infinite (%)0.0%
Mean42.76110124
Minimum1
Maximum56
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:08.147224image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19
Q134
median47
Q355
95-th percentile56
Maximum56
Range55
Interquartile range (IQR)21

Descriptive statistics

Standard deviation13.47189853
Coefficient of variation (CV)0.3150503177
Kurtosis0.01651112706
Mean42.76110124
Median Absolute Deviation (MAD)9
Skewness-0.8428382697
Sum1155576
Variance181.4920501
MonotocityNot monotonic
2020-11-30T23:58:08.257492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
56613314.3%
 
5525205.9%
 
3614303.3%
 
3513283.1%
 
3112572.9%
 
5412392.9%
 
5312302.9%
 
5011662.7%
 
349512.2%
 
237501.8%
 
387111.7%
 
276751.6%
 
415971.4%
 
395201.2%
 
485081.2%
 
373930.9%
 
463880.9%
 
473410.8%
 
523400.8%
 
403170.7%
 
433020.7%
 
332990.7%
 
292880.7%
 
262870.7%
 
212400.6%
 
Other values (31)28146.6%
 
(Missing)1580936.9%
 
ValueCountFrequency (%) 
1680.2%
 
21300.3%
 
31140.3%
 
4450.1%
 
5470.1%
 
62400.6%
 
719< 0.1%
 
818< 0.1%
 
9500.1%
 
10280.1%
 
ValueCountFrequency (%) 
56613314.3%
 
5525205.9%
 
5412392.9%
 
5312302.9%
 
523400.8%
 
51970.2%
 
5011662.7%
 
4920< 0.1%
 
485081.2%
 
473410.8%
 

FINANZ_ANLEGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.375248056
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:08.355998image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.545170622
Coefficient of variation (CV)0.650530212
Kurtosis-1.029460659
Mean2.375248056
Median Absolute Deviation (MAD)1
Skewness0.7249220956
Sum101739
Variance2.38755225
MonotocityNot monotonic
2020-11-30T23:58:08.440729image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11848043.1%
 
2908621.2%
 
5834519.5%
 
3432610.1%
 
425966.1%
 
ValueCountFrequency (%) 
11848043.1%
 
2908621.2%
 
3432610.1%
 
425966.1%
 
5834519.5%
 
ValueCountFrequency (%) 
5834519.5%
 
425966.1%
 
3432610.1%
 
2908621.2%
 
11848043.1%
 

FINANZ_HAUSBAUER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.219480307
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:08.532648image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.288541655
Coefficient of variation (CV)0.4002328116
Kurtosis-1.040761095
Mean3.219480307
Median Absolute Deviation (MAD)1
Skewness-0.02454759108
Sum137900
Variance1.660339597
MonotocityNot monotonic
2020-11-30T23:58:08.617113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31386232.4%
 
51033724.1%
 
2835519.5%
 
4588013.7%
 
1439910.3%
 
ValueCountFrequency (%) 
1439910.3%
 
2835519.5%
 
31386232.4%
 
4588013.7%
 
51033724.1%
 
ValueCountFrequency (%) 
51033724.1%
 
4588013.7%
 
31386232.4%
 
2835519.5%
 
1439910.3%
 

FINANZ_MINIMALIST
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.739009642
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:08.709300image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.09310875
Coefficient of variation (CV)0.2923524822
Kurtosis-1.036859549
Mean3.739009642
Median Absolute Deviation (MAD)1
Skewness-0.2565075271
Sum160153
Variance1.194886739
MonotocityNot monotonic
2020-11-30T23:58:08.793422image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
51471034.3%
 
31414633.0%
 
4839819.6%
 
2499411.7%
 
15851.4%
 
ValueCountFrequency (%) 
15851.4%
 
2499411.7%
 
31414633.0%
 
4839819.6%
 
51471034.3%
 
ValueCountFrequency (%) 
51471034.3%
 
4839819.6%
 
31414633.0%
 
2499411.7%
 
15851.4%
 

FINANZ_SPARER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.858683725
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:08.884851image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.235200139
Coefficient of variation (CV)0.6645563857
Kurtosis-0.5105097187
Mean1.858683725
Median Absolute Deviation (MAD)0
Skewness1.052637468
Sum79613
Variance1.525719382
MonotocityNot monotonic
2020-11-30T23:58:08.968506image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
12624061.3%
 
4796018.6%
 
2565213.2%
 
323385.5%
 
56431.5%
 
ValueCountFrequency (%) 
12624061.3%
 
2565213.2%
 
323385.5%
 
4796018.6%
 
56431.5%
 
ValueCountFrequency (%) 
56431.5%
 
4796018.6%
 
323385.5%
 
2565213.2%
 
12624061.3%
 

FINANZ_UNAUFFAELLIGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.247916326
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:09.058496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.49618473
Coefficient of variation (CV)0.6655873764
Kurtosis-0.628329488
Mean2.247916326
Median Absolute Deviation (MAD)1
Skewness0.9310765646
Sum96285
Variance2.238568746
MonotocityNot monotonic
2020-11-30T23:58:09.144267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11932445.1%
 
21032924.1%
 
5786118.4%
 
3427810.0%
 
410412.4%
 
ValueCountFrequency (%) 
11932445.1%
 
21032924.1%
 
3427810.0%
 
410412.4%
 
5786118.4%
 
ValueCountFrequency (%) 
5786118.4%
 
410412.4%
 
3427810.0%
 
21032924.1%
 
11932445.1%
 

FINANZ_VORSORGER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.261854178
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:09.239736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9859283044
Coefficient of variation (CV)0.2313378786
Kurtosis0.5956859639
Mean4.261854178
Median Absolute Deviation (MAD)0
Skewness-1.145411282
Sum182548
Variance0.9720546213
MonotocityNot monotonic
2020-11-30T23:58:09.321636image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52458157.4%
 
3917821.4%
 
4738717.2%
 
28742.0%
 
18131.9%
 
ValueCountFrequency (%) 
18131.9%
 
28742.0%
 
3917821.4%
 
4738717.2%
 
52458157.4%
 
ValueCountFrequency (%) 
52458157.4%
 
4738717.2%
 
3917821.4%
 
28742.0%
 
18131.9%
 

FINANZTYP
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.283076133
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:09.406173image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median5
Q36
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.671750369
Coefficient of variation (CV)0.3903153522
Kurtosis-1.296009315
Mean4.283076133
Median Absolute Deviation (MAD)1
Skewness-0.4613892446
Sum183457
Variance2.794749297
MonotocityNot monotonic
2020-11-30T23:58:09.493238image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
61528135.7%
 
21061724.8%
 
5744517.4%
 
4732617.1%
 
112422.9%
 
39222.2%
 
ValueCountFrequency (%) 
112422.9%
 
21061724.8%
 
39222.2%
 
4732617.1%
 
5744517.4%
 
61528135.7%
 
ValueCountFrequency (%) 
61528135.7%
 
5744517.4%
 
4732617.1%
 
39222.2%
 
21061724.8%
 
112422.9%
 

FIRMENDICHTE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean3.573084133
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:09.578338image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.091437469
Coefficient of variation (CV)0.3054608926
Kurtosis-0.5430420164
Mean3.573084133
Median Absolute Deviation (MAD)1
Skewness-0.4718726765
Sum125794
Variance1.191235748
MonotocityNot monotonic
2020-11-30T23:58:09.660875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
41298530.3%
 
3824719.3%
 
5750317.5%
 
2512712.0%
 
113443.1%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
113443.1%
 
2512712.0%
 
3824719.3%
 
41298530.3%
 
5750317.5%
 
ValueCountFrequency (%) 
5750317.5%
 
41298530.3%
 
3824719.3%
 
2512712.0%
 
113443.1%
 

GEBAEUDETYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean2.527665739
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:09.749244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q33
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.517545609
Coefficient of variation (CV)0.9959962546
Kurtosis0.6676348754
Mean2.527665739
Median Absolute Deviation (MAD)0
Skewness1.508743647
Sum88989
Variance6.338035892
MonotocityNot monotonic
2020-11-30T23:58:09.826899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
12226952.0%
 
3671615.7%
 
8564113.2%
 
24761.1%
 
4660.2%
 
6380.1%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
12226952.0%
 
24761.1%
 
3671615.7%
 
4660.2%
 
6380.1%
 
8564113.2%
 
ValueCountFrequency (%) 
8564113.2%
 
6380.1%
 
4660.2%
 
3671615.7%
 
24761.1%
 
12226952.0%
 

GEBAEUDETYP_RASTER
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean3.815258763
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:09.914113image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8808983516
Coefficient of variation (CV)0.2308882323
Kurtosis0.3812248941
Mean3.815258763
Median Absolute Deviation (MAD)1
Skewness-0.6299812693
Sum134320
Variance0.7759819058
MonotocityNot monotonic
2020-11-30T23:58:10.001043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
41670339.0%
 
3849119.8%
 
5750317.5%
 
220114.7%
 
14981.2%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
14981.2%
 
220114.7%
 
3849119.8%
 
41670339.0%
 
5750317.5%
 
ValueCountFrequency (%) 
5750317.5%
 
41670339.0%
 
3849119.8%
 
220114.7%
 
14981.2%
 

GEBURTSJAHR
Real number (ℝ≥0)

ZEROS

Distinct106
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1148.488595
Minimum0
Maximum2017
Zeros17583
Zeros (%)41.1%
Memory size334.8 KiB
2020-11-30T23:58:10.117903image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1934
Q31950
95-th percentile1970
Maximum2017
Range2017
Interquartile range (IQR)1950

Descriptive statistics

Standard deviation958.471276
Coefficient of variation (CV)0.8345501035
Kurtosis-1.867392281
Mean1148.488595
Median Absolute Deviation (MAD)30
Skewness-0.3634399814
Sum49193212
Variance918667.187
MonotocityNot monotonic
2020-11-30T23:58:10.241808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
01758341.1%
 
19419152.1%
 
19398662.0%
 
19388442.0%
 
19407691.8%
 
19377221.7%
 
19367011.6%
 
19426821.6%
 
19436641.6%
 
19356471.5%
 
19446381.5%
 
19346181.4%
 
19495881.4%
 
19505851.4%
 
19485801.4%
 
19515651.3%
 
19475571.3%
 
19525431.3%
 
19545391.3%
 
19535261.2%
 
19565181.2%
 
19334961.2%
 
19554921.1%
 
19464801.1%
 
19574801.1%
 
Other values (81)1023523.9%
 
ValueCountFrequency (%) 
01758341.1%
 
19001< 0.1%
 
19031< 0.1%
 
19041< 0.1%
 
19071< 0.1%
 
19092< 0.1%
 
19101< 0.1%
 
19111< 0.1%
 
19136< 0.1%
 
191410< 0.1%
 
ValueCountFrequency (%) 
20179< 0.1%
 
20162< 0.1%
 
20156< 0.1%
 
20141< 0.1%
 
20135< 0.1%
 
20129< 0.1%
 
20091< 0.1%
 
20051< 0.1%
 
20032< 0.1%
 
20011< 0.1%
 

GEMEINDETYP
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing7784
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean25.40400582
Minimum11
Maximum50
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:10.350742image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q112
median22
Q340
95-th percentile50
Maximum50
Range39
Interquartile range (IQR)28

Descriptive statistics

Standard deviation12.58014626
Coefficient of variation (CV)0.4952032504
Kurtosis-0.9453877947
Mean25.40400582
Median Absolute Deviation (MAD)10
Skewness0.4689845605
Sum890385
Variance158.2600798
MonotocityNot monotonic
2020-11-30T23:58:10.433301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
11686616.0%
 
22644715.1%
 
40619314.5%
 
30567513.2%
 
1242439.9%
 
5029666.9%
 
2126596.2%
 
(Missing)778418.2%
 
ValueCountFrequency (%) 
11686616.0%
 
1242439.9%
 
2126596.2%
 
22644715.1%
 
30567513.2%
 
40619314.5%
 
5029666.9%
 
ValueCountFrequency (%) 
5029666.9%
 
40619314.5%
 
30567513.2%
 
22644715.1%
 
2126596.2%
 
1242439.9%
 
11686616.0%
 

GFK_URLAUBERTYP
Real number (ℝ≥0)

MISSING

Distinct12
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean6.493669388
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:10.539169image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.032499593
Coefficient of variation (CV)0.4669932225
Kurtosis-1.009915883
Mean6.493669388
Median Absolute Deviation (MAD)2
Skewness0.1699089557
Sum274390
Variance9.196053783
MonotocityNot monotonic
2020-11-30T23:58:10.628836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
5964422.5%
 
10611614.3%
 
8432110.1%
 
4431010.1%
 
338058.9%
 
732107.5%
 
1224595.7%
 
1119834.6%
 
118494.3%
 
617364.1%
 
914413.4%
 
213813.2%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
118494.3%
 
213813.2%
 
338058.9%
 
4431010.1%
 
5964422.5%
 
617364.1%
 
732107.5%
 
8432110.1%
 
914413.4%
 
10611614.3%
 
ValueCountFrequency (%) 
1224595.7%
 
1119834.6%
 
10611614.3%
 
914413.4%
 
8432110.1%
 
732107.5%
 
617364.1%
 
5964422.5%
 
4431010.1%
 
338058.9%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size334.8 KiB
0
30804 
1
12029 
ValueCountFrequency (%) 
03080471.9%
 
11202928.1%
 

HEALTH_TYP
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size334.8 KiB
2
16826 
1
10532 
3
8143 
-1
7332 
ValueCountFrequency (%) 
21682639.3%
 
11053224.6%
 
3814319.0%
 
-1733217.1%
 
2020-11-30T23:58:10.734162image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
11786435.6%
 
21682633.5%
 
3814316.2%
 
-733214.6%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number4283385.4%
 
Dash Punctuation733214.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
11786441.7%
 
21682639.3%
 
3814319.0%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-7332100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common50165100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
11786435.6%
 
21682633.5%
 
3814316.2%
 
-733214.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII50165100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
11786435.6%
 
21682633.5%
 
3814316.2%
 
-733214.6%
 

HH_DELTA_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing9619
Missing (%)22.5%
Memory size334.8 KiB
0
28798 
1
4416 
(Missing)
9619 
ValueCountFrequency (%) 
02879867.2%
 
1441610.3%
 
(Missing)961922.5%
 

HH_EINKOMMEN_SCORE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing642
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean3.569979379
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:10.830141image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.662756116
Coefficient of variation (CV)0.465760706
Kurtosis-1.336480156
Mean3.569979379
Median Absolute Deviation (MAD)2
Skewness0.03997769873
Sum150621
Variance2.764757902
MonotocityNot monotonic
2020-11-30T23:58:10.933154image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21112626.0%
 
5781718.2%
 
6708316.5%
 
4693116.2%
 
3491411.5%
 
1432010.1%
 
(Missing)6421.5%
 
ValueCountFrequency (%) 
1432010.1%
 
21112626.0%
 
3491411.5%
 
4693116.2%
 
5781718.2%
 
6708316.5%
 
ValueCountFrequency (%) 
6708316.5%
 
5781718.2%
 
4693116.2%
 
3491411.5%
 
21112626.0%
 
1432010.1%
 

INNENSTADT
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing7641
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean4.76551489
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:11.026174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q36
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.022486114
Coefficient of variation (CV)0.4244003347
Kurtosis-0.9339372748
Mean4.76551489
Median Absolute Deviation (MAD)2
Skewness-0.04074678704
Sum167708
Variance4.090450083
MonotocityNot monotonic
2020-11-30T23:58:11.122604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
5647915.1%
 
4588713.7%
 
6519512.1%
 
8437010.2%
 
2430210.0%
 
338068.9%
 
734108.0%
 
117434.1%
 
(Missing)764117.8%
 
ValueCountFrequency (%) 
117434.1%
 
2430210.0%
 
338068.9%
 
4588713.7%
 
5647915.1%
 
6519512.1%
 
734108.0%
 
8437010.2%
 
ValueCountFrequency (%) 
8437010.2%
 
734108.0%
 
6519512.1%
 
5647915.1%
 
4588713.7%
 
338068.9%
 
2430210.0%
 
117434.1%
 

KBA05_ALTER1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.801609517
Minimum0
Maximum9
Zeros5183
Zeros (%)12.1%
Memory size334.8 KiB
2020-11-30T23:58:11.231528image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.332318903
Coefficient of variation (CV)0.7395159109
Kurtosis7.268434611
Mean1.801609517
Median Absolute Deviation (MAD)1
Skewness1.655347741
Sum61788
Variance1.77507366
MonotocityNot monotonic
2020-11-30T23:58:11.324459image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21104625.8%
 
1930721.7%
 
3650115.2%
 
0518312.1%
 
418894.4%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
0518312.1%
 
1930721.7%
 
21104625.8%
 
3650115.2%
 
418894.4%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
418894.4%
 
3650115.2%
 
21104625.8%
 
1930721.7%
 
0518312.1%
 

KBA05_ALTER2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.892611383
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:11.419861image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.194333315
Coefficient of variation (CV)0.4128910374
Kurtosis5.741431821
Mean2.892611383
Median Absolute Deviation (MAD)1
Skewness1.381510434
Sum99205
Variance1.426432067
MonotocityNot monotonic
2020-11-30T23:58:11.521854image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31370532.0%
 
2891520.8%
 
4604814.1%
 
133887.9%
 
518704.4%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
133887.9%
 
2891520.8%
 
31370532.0%
 
4604814.1%
 
518704.4%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
518704.4%
 
4604814.1%
 
31370532.0%
 
2891520.8%
 
133887.9%
 

KBA05_ALTER3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.136896431
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:11.632403image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.203826712
Coefficient of variation (CV)0.3837636144
Kurtosis4.535292967
Mean3.136896431
Median Absolute Deviation (MAD)1
Skewness1.110996968
Sum107583
Variance1.449198754
MonotocityNot monotonic
2020-11-30T23:58:11.735583image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31393132.5%
 
4763517.8%
 
2668415.6%
 
532197.5%
 
124575.7%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
124575.7%
 
2668415.6%
 
31393132.5%
 
4763517.8%
 
532197.5%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
532197.5%
 
4763517.8%
 
31393132.5%
 
2668415.6%
 
124575.7%
 

KBA05_ALTER4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.21748892
Minimum0
Maximum9
Zeros819
Zeros (%)1.9%
Memory size334.8 KiB
2020-11-30T23:58:11.839255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.251874234
Coefficient of variation (CV)0.389084241
Kurtosis4.02064627
Mean3.21748892
Median Absolute Deviation (MAD)1
Skewness0.6465227466
Sum110347
Variance1.567189099
MonotocityNot monotonic
2020-11-30T23:58:11.926278image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31440733.6%
 
4829919.4%
 
2507511.8%
 
537818.8%
 
115453.6%
 
08191.9%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
08191.9%
 
115453.6%
 
2507511.8%
 
31440733.6%
 
4829919.4%
 
537818.8%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
537818.8%
 
4829919.4%
 
31440733.6%
 
2507511.8%
 
115453.6%
 
08191.9%
 

KBA05_ANHANG
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.195358059
Minimum0
Maximum9
Zeros9844
Zeros (%)23.0%
Memory size334.8 KiB
2020-11-30T23:58:12.014803image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.254879393
Coefficient of variation (CV)1.049793728
Kurtosis12.87027552
Mean1.195358059
Median Absolute Deviation (MAD)1
Skewness2.614223465
Sum40996
Variance1.574722292
MonotocityNot monotonic
2020-11-30T23:58:12.091087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11514735.4%
 
0984423.0%
 
3483111.3%
 
241309.6%
 
93440.8%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
0984423.0%
 
11514735.4%
 
241309.6%
 
3483111.3%
 
93440.8%
 
ValueCountFrequency (%) 
93440.8%
 
3483111.3%
 
241309.6%
 
11514735.4%
 
0984423.0%
 

KBA05_ANTG1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.847241661
Minimum0
Maximum4
Zeros9113
Zeros (%)21.3%
Memory size334.8 KiB
2020-11-30T23:58:12.168798image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.446733168
Coefficient of variation (CV)0.7831856537
Kurtosis-1.354573989
Mean1.847241661
Median Absolute Deviation (MAD)1
Skewness0.07943410645
Sum63353
Variance2.093036858
MonotocityNot monotonic
2020-11-30T23:58:12.248189image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
0911321.3%
 
3698416.3%
 
2662815.5%
 
4585813.7%
 
1571313.3%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
0911321.3%
 
1571313.3%
 
2662815.5%
 
3698416.3%
 
4585813.7%
 
ValueCountFrequency (%) 
4585813.7%
 
3698416.3%
 
2662815.5%
 
1571313.3%
 
0911321.3%
 

KBA05_ANTG2
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.173926989
Minimum0
Maximum4
Zeros12881
Zeros (%)30.1%
Memory size334.8 KiB
2020-11-30T23:58:12.334930image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum4
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.154888133
Coefficient of variation (CV)0.983781908
Kurtosis-0.7166197434
Mean1.173926989
Median Absolute Deviation (MAD)1
Skewness0.6173699831
Sum40261
Variance1.333766599
MonotocityNot monotonic
2020-11-30T23:58:12.417431image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
01288130.1%
 
1917221.4%
 
2656315.3%
 
3475711.1%
 
49232.2%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
01288130.1%
 
1917221.4%
 
2656315.3%
 
3475711.1%
 
49232.2%
 
ValueCountFrequency (%) 
49232.2%
 
3475711.1%
 
2656315.3%
 
1917221.4%
 
01288130.1%
 

KBA05_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Memory size334.8 KiB
0
25982 
1
3011 
3
2696 
2
2607 
ValueCountFrequency (%) 
02598260.7%
 
130117.0%
 
326966.3%
 
226076.1%
 
(Missing)853719.9%
 
2020-11-30T23:58:12.517476image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
06027846.9%
 
.3429626.7%
 
n1707413.3%
 
a85376.6%
 
130112.3%
 
326962.1%
 
226072.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6859253.4%
 
Other Punctuation3429626.7%
 
Lowercase Letter2561119.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
06027887.9%
 
130114.4%
 
326963.9%
 
226073.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34296100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10288880.1%
 
Latin2561119.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
06027858.6%
 
.3429633.3%
 
130112.9%
 
326962.6%
 
226072.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
06027846.9%
 
.3429626.7%
 
n1707413.3%
 
a85376.6%
 
130112.3%
 
326962.1%
 
226072.0%
 

KBA05_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Memory size334.8 KiB
0
28923 
1
 
2704
2
 
2669
ValueCountFrequency (%) 
02892367.5%
 
127046.3%
 
226696.2%
 
(Missing)853719.9%
 
2020-11-30T23:58:12.613734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
06321949.2%
 
.3429626.7%
 
n1707413.3%
 
a85376.6%
 
127042.1%
 
226692.1%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6859253.4%
 
Other Punctuation3429626.7%
 
Lowercase Letter2561119.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
06321992.2%
 
127043.9%
 
226693.9%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34296100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10288880.1%
 
Latin2561119.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
06321961.4%
 
.3429633.3%
 
127042.6%
 
226692.6%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
06321949.2%
 
.3429626.7%
 
n1707413.3%
 
a85376.6%
 
127042.1%
 
226692.1%
 

KBA05_AUTOQUOT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.421827618
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:12.699149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.224172391
Coefficient of variation (CV)0.3577539628
Kurtosis3.310569277
Mean3.421827618
Median Absolute Deviation (MAD)1
Skewness0.659811035
Sum117355
Variance1.498598042
MonotocityNot monotonic
2020-11-30T23:58:12.780174image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31153726.9%
 
41089825.4%
 
5502111.7%
 
242399.9%
 
122305.2%
 
93710.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
122305.2%
 
242399.9%
 
31153726.9%
 
41089825.4%
 
5502111.7%
 
93710.9%
 
ValueCountFrequency (%) 
93710.9%
 
5502111.7%
 
41089825.4%
 
31153726.9%
 
242399.9%
 
122305.2%
 

KBA05_BAUMAX
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.224982505
Minimum0
Maximum5
Zeros14287
Zeros (%)33.4%
Memory size334.8 KiB
2020-11-30T23:58:12.866430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.589806013
Coefficient of variation (CV)1.297819362
Kurtosis0.6737791009
Mean1.224982505
Median Absolute Deviation (MAD)1
Skewness1.397068119
Sum42012
Variance2.527483161
MonotocityNot monotonic
2020-11-30T23:58:12.956091image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
01428733.4%
 
11282529.9%
 
533087.7%
 
322555.3%
 
413203.1%
 
23010.7%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
01428733.4%
 
11282529.9%
 
23010.7%
 
322555.3%
 
413203.1%
 
533087.7%
 
ValueCountFrequency (%) 
533087.7%
 
413203.1%
 
322555.3%
 
23010.7%
 
11282529.9%
 
01428733.4%
 

KBA05_CCM1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.988774201
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:13.040581image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.204533862
Coefficient of variation (CV)0.4030193587
Kurtosis5.095423615
Mean2.988774201
Median Absolute Deviation (MAD)1
Skewness1.272344205
Sum102503
Variance1.450901824
MonotocityNot monotonic
2020-11-30T23:58:13.123629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31373732.1%
 
2823219.2%
 
4653915.3%
 
129376.9%
 
524815.8%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
129376.9%
 
2823219.2%
 
31373732.1%
 
4653915.3%
 
524815.8%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
524815.8%
 
4653915.3%
 
31373732.1%
 
2823219.2%
 
129376.9%
 

KBA05_CCM2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.083537439
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:13.212421image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.172107001
Coefficient of variation (CV)0.3801176488
Kurtosis5.437379051
Mean3.083537439
Median Absolute Deviation (MAD)1
Skewness1.25073368
Sum105753
Variance1.373834823
MonotocityNot monotonic
2020-11-30T23:58:13.296819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31428233.3%
 
4769118.0%
 
2715616.7%
 
524265.7%
 
123715.5%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
123715.5%
 
2715616.7%
 
31428233.3%
 
4769118.0%
 
524265.7%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
524265.7%
 
4769118.0%
 
31428233.3%
 
2715616.7%
 
123715.5%
 

KBA05_CCM3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.110858409
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:13.384709image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.209098475
Coefficient of variation (CV)0.3886703657
Kurtosis4.505965676
Mean3.110858409
Median Absolute Deviation (MAD)1
Skewness1.117404785
Sum106690
Variance1.461919123
MonotocityNot monotonic
2020-11-30T23:58:13.466274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31345231.4%
 
4774218.1%
 
2714416.7%
 
530407.1%
 
125485.9%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
125485.9%
 
2714416.7%
 
31345231.4%
 
4774218.1%
 
530407.1%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
530407.1%
 
4774218.1%
 
31345231.4%
 
2714416.7%
 
125485.9%
 

KBA05_CCM4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.340447866
Minimum0
Maximum9
Zeros11018
Zeros (%)25.7%
Memory size334.8 KiB
2020-11-30T23:58:13.555802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.431763581
Coefficient of variation (CV)1.068123288
Kurtosis7.010572229
Mean1.340447866
Median Absolute Deviation (MAD)1
Skewness1.957542887
Sum45972
Variance2.049946952
MonotocityNot monotonic
2020-11-30T23:58:13.626669image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
01101825.7%
 
11101525.7%
 
2613414.3%
 
336778.6%
 
420824.9%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
01101825.7%
 
11101525.7%
 
2613414.3%
 
336778.6%
 
420824.9%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
420824.9%
 
336778.6%
 
2613414.3%
 
11101525.7%
 
01101825.7%
 

KBA05_DIESEL
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.088815022
Minimum0
Maximum9
Zeros2427
Zeros (%)5.7%
Memory size334.8 KiB
2020-11-30T23:58:13.703719image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.245765177
Coefficient of variation (CV)0.5963980363
Kurtosis8.398236635
Mean2.088815022
Median Absolute Deviation (MAD)1
Skewness1.725893014
Sum71638
Variance1.551930877
MonotocityNot monotonic
2020-11-30T23:58:13.779745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21375732.1%
 
3756917.7%
 
1753517.6%
 
426386.2%
 
024275.7%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
024275.7%
 
1753517.6%
 
21375732.1%
 
3756917.7%
 
426386.2%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
426386.2%
 
3756917.7%
 
21375732.1%
 
1753517.6%
 
024275.7%
 

KBA05_FRAU
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.064584791
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:13.860653image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.186230284
Coefficient of variation (CV)0.3870769988
Kurtosis5.222909212
Mean3.064584791
Median Absolute Deviation (MAD)1
Skewness1.248418138
Sum105103
Variance1.407142286
MonotocityNot monotonic
2020-11-30T23:58:13.945514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31468834.3%
 
2713216.7%
 
4682515.9%
 
527166.3%
 
125656.0%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
125656.0%
 
2713216.7%
 
31468834.3%
 
4682515.9%
 
527166.3%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
527166.3%
 
4682515.9%
 
31468834.3%
 
2713216.7%
 
125656.0%
 

KBA05_GBZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.405090973
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:14.036949image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.302426001
Coefficient of variation (CV)0.382493746
Kurtosis-0.9288659201
Mean3.405090973
Median Absolute Deviation (MAD)1
Skewness-0.3917334283
Sum116781
Variance1.696313489
MonotocityNot monotonic
2020-11-30T23:58:14.117668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
4883320.6%
 
5872920.4%
 
3816419.1%
 
2474211.1%
 
138288.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
138288.9%
 
2474211.1%
 
3816419.1%
 
4883320.6%
 
5872920.4%
 
ValueCountFrequency (%) 
5872920.4%
 
4883320.6%
 
3816419.1%
 
2474211.1%
 
138288.9%
 

KBA05_HERST1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.496821787
Minimum0
Maximum9
Zeros2594
Zeros (%)6.1%
Memory size334.8 KiB
2020-11-30T23:58:14.206401image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median2
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.489092906
Coefficient of variation (CV)0.5963953512
Kurtosis2.474797639
Mean2.496821787
Median Absolute Deviation (MAD)1
Skewness0.8913860665
Sum85631
Variance2.217397684
MonotocityNot monotonic
2020-11-30T23:58:14.280768image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
21048724.5%
 
3825319.3%
 
1553212.9%
 
4426410.0%
 
527966.5%
 
025946.1%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
025946.1%
 
1553212.9%
 
21048724.5%
 
3825319.3%
 
4426410.0%
 
527966.5%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
527966.5%
 
4426410.0%
 
3825319.3%
 
21048724.5%
 
1553212.9%
 
025946.1%
 

KBA05_HERST2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.101294612
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:14.358268image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.171614793
Coefficient of variation (CV)0.3777824874
Kurtosis5.344168201
Mean3.101294612
Median Absolute Deviation (MAD)1
Skewness1.291102635
Sum106362
Variance1.372681222
MonotocityNot monotonic
2020-11-30T23:58:14.440553image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31413133.0%
 
2761417.8%
 
4741017.3%
 
527506.4%
 
120214.7%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
120214.7%
 
2761417.8%
 
31413133.0%
 
4741017.3%
 
527506.4%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
527506.4%
 
4741017.3%
 
31413133.0%
 
2761417.8%
 
120214.7%
 

KBA05_HERST3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.941275951
Minimum0
Maximum9
Zeros519
Zeros (%)1.2%
Memory size334.8 KiB
2020-11-30T23:58:14.534788image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.24410527
Coefficient of variation (CV)0.4229814852
Kurtosis4.731515197
Mean2.941275951
Median Absolute Deviation (MAD)1
Skewness1.037995662
Sum100874
Variance1.547797923
MonotocityNot monotonic
2020-11-30T23:58:14.611966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31403832.8%
 
2770918.0%
 
4638014.9%
 
129777.0%
 
523035.4%
 
05191.2%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
05191.2%
 
129777.0%
 
2770918.0%
 
31403832.8%
 
4638014.9%
 
523035.4%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
523035.4%
 
4638014.9%
 
31403832.8%
 
2770918.0%
 
129777.0%
 
05191.2%
 

KBA05_HERST4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.889404012
Minimum0
Maximum9
Zeros1045
Zeros (%)2.4%
Memory size334.8 KiB
2020-11-30T23:58:14.694824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.355613508
Coefficient of variation (CV)0.4691671718
Kurtosis3.11966744
Mean2.889404012
Median Absolute Deviation (MAD)1
Skewness0.7674051574
Sum99095
Variance1.837687984
MonotocityNot monotonic
2020-11-30T23:58:14.770303image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31201728.1%
 
2785818.3%
 
4638814.9%
 
136618.5%
 
529576.9%
 
010452.4%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
010452.4%
 
136618.5%
 
2785818.3%
 
31201728.1%
 
4638814.9%
 
529576.9%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
529576.9%
 
4638814.9%
 
31201728.1%
 
2785818.3%
 
136618.5%
 
010452.4%
 

KBA05_HERST5
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.861616515
Minimum0
Maximum9
Zeros1654
Zeros (%)3.9%
Memory size334.8 KiB
2020-11-30T23:58:14.852844image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.392743906
Coefficient of variation (CV)0.4866983045
Kurtosis2.802398122
Mean2.861616515
Median Absolute Deviation (MAD)1
Skewness0.6169398439
Sum98142
Variance1.939735588
MonotocityNot monotonic
2020-11-30T23:58:14.928276image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31134326.5%
 
2782418.3%
 
4709016.6%
 
133257.8%
 
526906.3%
 
016543.9%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
016543.9%
 
133257.8%
 
2782418.3%
 
31134326.5%
 
4709016.6%
 
526906.3%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
526906.3%
 
4709016.6%
 
31134326.5%
 
2782418.3%
 
133257.8%
 
016543.9%
 

KBA05_HERSTTEMP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean2.678378685
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:15.009100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.342299937
Coefficient of variation (CV)0.5011613719
Kurtosis4.771824061
Mean2.678378685
Median Absolute Deviation (MAD)1
Skewness1.384898275
Sum94295
Variance1.80176912
MonotocityNot monotonic
2020-11-30T23:58:15.092892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31212628.3%
 
2831919.4%
 
1731417.1%
 
4517412.1%
 
517974.2%
 
94761.1%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
1731417.1%
 
2831919.4%
 
31212628.3%
 
4517412.1%
 
517974.2%
 
94761.1%
 
ValueCountFrequency (%) 
94761.1%
 
517974.2%
 
4517412.1%
 
31212628.3%
 
2831919.4%
 
1731417.1%
 

KBA05_KRSAQUOT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.280382552
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:15.183805image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.236796031
Coefficient of variation (CV)0.3770279873
Kurtosis3.476435156
Mean3.280382552
Median Absolute Deviation (MAD)1
Skewness0.8558414349
Sum112504
Variance1.529664423
MonotocityNot monotonic
2020-11-30T23:58:15.266194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31346831.4%
 
4818219.1%
 
2515012.0%
 
5465410.9%
 
124725.8%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
124725.8%
 
2515012.0%
 
31346831.4%
 
4818219.1%
 
5465410.9%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
5465410.9%
 
4818219.1%
 
31346831.4%
 
2515012.0%
 
124725.8%
 

KBA05_KRSHERST1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.0563331
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:15.353998image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.152406591
Coefficient of variation (CV)0.3770552992
Kurtosis6.023068344
Mean3.0563331
Median Absolute Deviation (MAD)1
Skewness1.351754089
Sum104820
Variance1.328040952
MonotocityNot monotonic
2020-11-30T23:58:15.438089image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31426433.3%
 
4773918.1%
 
2769918.0%
 
121945.1%
 
520304.7%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
121945.1%
 
2769918.0%
 
31426433.3%
 
4773918.1%
 
520304.7%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
520304.7%
 
4773918.1%
 
31426433.3%
 
2769918.0%
 
121945.1%
 

KBA05_KRSHERST2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.077035223
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:15.527307image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.200870474
Coefficient of variation (CV)0.3902686797
Kurtosis4.828861754
Mean3.077035223
Median Absolute Deviation (MAD)1
Skewness1.163356247
Sum105530
Variance1.442089895
MonotocityNot monotonic
2020-11-30T23:58:15.609539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31395432.6%
 
4743717.4%
 
2707916.5%
 
527446.4%
 
127126.3%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
127126.3%
 
2707916.5%
 
31395432.6%
 
4743717.4%
 
527446.4%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
527446.4%
 
4743717.4%
 
31395432.6%
 
2707916.5%
 
127126.3%
 

KBA05_KRSHERST3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.081875437
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:15.699166image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.222810056
Coefficient of variation (CV)0.3967746527
Kurtosis4.363059243
Mean3.081875437
Median Absolute Deviation (MAD)1
Skewness1.143460428
Sum105696
Variance1.495264434
MonotocityNot monotonic
2020-11-30T23:58:15.781627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31382032.3%
 
2737917.2%
 
4669915.6%
 
533317.8%
 
126976.3%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
126976.3%
 
2737917.2%
 
31382032.3%
 
4669915.6%
 
533317.8%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
533317.8%
 
4669915.6%
 
31382032.3%
 
2737917.2%
 
126976.3%
 

KBA05_KRSKLEIN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Memory size334.8 KiB
2
20907 
1
6787 
3
6232 
9
 
370
ValueCountFrequency (%) 
22090748.8%
 
1678715.8%
 
3623214.5%
 
93700.9%
 
(Missing)853719.9%
 
2020-11-30T23:58:15.885906image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
22090716.3%
 
n1707413.3%
 
a85376.6%
 
167875.3%
 
362324.8%
 
93700.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6859253.4%
 
Other Punctuation3429626.7%
 
Lowercase Letter2561119.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03429650.0%
 
22090730.5%
 
167879.9%
 
362329.1%
 
93700.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34296100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10288880.1%
 
Latin2561119.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3429633.3%
 
03429633.3%
 
22090720.3%
 
167876.6%
 
362326.1%
 
93700.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
22090716.3%
 
n1707413.3%
 
a85376.6%
 
167875.3%
 
362324.8%
 
93700.3%
 

KBA05_KRSOBER
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Memory size334.8 KiB
2
22399 
3
5777 
1
5750 
9
 
370
ValueCountFrequency (%) 
22239952.3%
 
3577713.5%
 
1575013.4%
 
93700.9%
 
(Missing)853719.9%
 
2020-11-30T23:58:15.982084image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
22239917.4%
 
n1707413.3%
 
a85376.6%
 
357774.5%
 
157504.5%
 
93700.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6859253.4%
 
Other Punctuation3429626.7%
 
Lowercase Letter2561119.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03429650.0%
 
22239932.7%
 
357778.4%
 
157508.4%
 
93700.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34296100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10288880.1%
 
Latin2561119.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3429633.3%
 
03429633.3%
 
22239921.8%
 
357775.6%
 
157505.6%
 
93700.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
22239917.4%
 
n1707413.3%
 
a85376.6%
 
357774.5%
 
157504.5%
 
93700.3%
 

KBA05_KRSVAN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Memory size334.8 KiB
2
23728 
3
5482 
1
4716 
9
 
370
ValueCountFrequency (%) 
22372855.4%
 
3548212.8%
 
1471611.0%
 
93700.9%
 
(Missing)853719.9%
 
2020-11-30T23:58:16.072672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
22372818.5%
 
n1707413.3%
 
a85376.6%
 
354824.3%
 
147163.7%
 
93700.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6859253.4%
 
Other Punctuation3429626.7%
 
Lowercase Letter2561119.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03429650.0%
 
22372834.6%
 
354828.0%
 
147166.9%
 
93700.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34296100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10288880.1%
 
Latin2561119.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3429633.3%
 
03429633.3%
 
22372823.1%
 
354825.3%
 
147164.6%
 
93700.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
22372818.5%
 
n1707413.3%
 
a85376.6%
 
354824.3%
 
147163.7%
 
93700.3%
 

KBA05_KRSZUL
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Memory size334.8 KiB
2
18468 
1
8157 
3
7301 
9
 
370
ValueCountFrequency (%) 
21846843.1%
 
1815719.0%
 
3730117.0%
 
93700.9%
 
(Missing)853719.9%
 
2020-11-30T23:58:16.170994image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
21846814.4%
 
n1707413.3%
 
a85376.6%
 
181576.3%
 
373015.7%
 
93700.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6859253.4%
 
Other Punctuation3429626.7%
 
Lowercase Letter2561119.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03429650.0%
 
21846826.9%
 
1815711.9%
 
3730110.6%
 
93700.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34296100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10288880.1%
 
Latin2561119.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3429633.3%
 
03429633.3%
 
21846817.9%
 
181577.9%
 
373017.1%
 
93700.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
21846814.4%
 
n1707413.3%
 
a85376.6%
 
181576.3%
 
373015.7%
 
93700.3%
 

KBA05_KW1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.953872172
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:16.260087image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.231257218
Coefficient of variation (CV)0.4168281992
Kurtosis4.652270474
Mean2.953872172
Median Absolute Deviation (MAD)1
Skewness1.173556787
Sum101306
Variance1.515994337
MonotocityNot monotonic
2020-11-30T23:58:16.340727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31308030.5%
 
2797518.6%
 
4690516.1%
 
136668.6%
 
523005.4%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
136668.6%
 
2797518.6%
 
31308030.5%
 
4690516.1%
 
523005.4%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
523005.4%
 
4690516.1%
 
31308030.5%
 
2797518.6%
 
136668.6%
 

KBA05_KW2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.12120947
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:16.427336image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.176098807
Coefficient of variation (CV)0.3768086757
Kurtosis5.198494507
Mean3.12120947
Median Absolute Deviation (MAD)1
Skewness1.23089287
Sum107045
Variance1.383208404
MonotocityNot monotonic
2020-11-30T23:58:16.511416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31460834.1%
 
4739017.3%
 
2682715.9%
 
528946.8%
 
122075.2%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
122075.2%
 
2682715.9%
 
31460834.1%
 
4739017.3%
 
528946.8%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
528946.8%
 
4739017.3%
 
31460834.1%
 
2682715.9%
 
122075.2%
 

KBA05_KW3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.561552368
Minimum0
Maximum9
Zeros7876
Zeros (%)18.4%
Memory size334.8 KiB
2020-11-30T23:58:16.601644image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.429165953
Coefficient of variation (CV)0.9152212777
Kurtosis6.083884754
Mean1.561552368
Median Absolute Deviation (MAD)1
Skewness1.741109883
Sum53555
Variance2.042515322
MonotocityNot monotonic
2020-11-30T23:58:16.678904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11156827.0%
 
0787618.4%
 
2766217.9%
 
339479.2%
 
428736.7%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
0787618.4%
 
11156827.0%
 
2766217.9%
 
339479.2%
 
428736.7%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
428736.7%
 
339479.2%
 
2766217.9%
 
11156827.0%
 
0787618.4%
 

KBA05_MAXAH
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.659902029
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:16.759732image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median4
Q35
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.354447053
Coefficient of variation (CV)0.370077407
Kurtosis0.9141816494
Mean3.659902029
Median Absolute Deviation (MAD)1
Skewness0.35900663
Sum125520
Variance1.834526819
MonotocityNot monotonic
2020-11-30T23:58:16.839868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
51202728.1%
 
3922421.5%
 
2628514.7%
 
4514112.0%
 
112492.9%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
112492.9%
 
2628514.7%
 
3922421.5%
 
4514112.0%
 
51202728.1%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
51202728.1%
 
4514112.0%
 
3922421.5%
 
2628514.7%
 
112492.9%
 

KBA05_MAXBJ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.484954514
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:16.931161image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.361737744
Coefficient of variation (CV)0.5479930264
Kurtosis3.507509824
Mean2.484954514
Median Absolute Deviation (MAD)1
Skewness1.163914073
Sum85224
Variance1.854329684
MonotocityNot monotonic
2020-11-30T23:58:17.012830image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11036624.2%
 
4937821.9%
 
2853019.9%
 
3565213.2%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
11036624.2%
 
2853019.9%
 
3565213.2%
 
4937821.9%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
4937821.9%
 
3565213.2%
 
2853019.9%
 
11036624.2%
 

KBA05_MAXHERST
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.772743177
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:17.101717image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.28463687
Coefficient of variation (CV)0.4633090006
Kurtosis4.296034549
Mean2.772743177
Median Absolute Deviation (MAD)1
Skewness1.417271357
Sum95094
Variance1.650291889
MonotocityNot monotonic
2020-11-30T23:58:17.189393image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21309530.6%
 
3906821.2%
 
4503311.8%
 
138539.0%
 
528776.7%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
138539.0%
 
21309530.6%
 
3906821.2%
 
4503311.8%
 
528776.7%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
528776.7%
 
4503311.8%
 
3906821.2%
 
21309530.6%
 
138539.0%
 

KBA05_MAXSEG
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.227052718
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:17.282030image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.146493103
Coefficient of variation (CV)0.5148028576
Kurtosis11.03137673
Mean2.227052718
Median Absolute Deviation (MAD)1
Skewness2.308096112
Sum76379
Variance1.314446435
MonotocityNot monotonic
2020-11-30T23:58:17.359464image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21435033.5%
 
1871320.3%
 
3781618.2%
 
430477.1%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
1871320.3%
 
21435033.5%
 
3781618.2%
 
430477.1%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
430477.1%
 
3781618.2%
 
21435033.5%
 
1871320.3%
 

KBA05_MAXVORB
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Memory size334.8 KiB
2
15982 
1
9763 
3
8181 
9
 
370
ValueCountFrequency (%) 
21598237.3%
 
1976322.8%
 
3818119.1%
 
93700.9%
 
(Missing)853719.9%
 
2020-11-30T23:58:17.465962image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
n1707413.3%
 
21598212.4%
 
197637.6%
 
a85376.6%
 
381816.4%
 
93700.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6859253.4%
 
Other Punctuation3429626.7%
 
Lowercase Letter2561119.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03429650.0%
 
21598223.3%
 
1976314.2%
 
3818111.9%
 
93700.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34296100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10288880.1%
 
Latin2561119.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3429633.3%
 
03429633.3%
 
21598215.5%
 
197639.5%
 
381818.0%
 
93700.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3429626.7%
 
03429626.7%
 
n1707413.3%
 
21598212.4%
 
197637.6%
 
a85376.6%
 
381816.4%
 
93700.3%
 

KBA05_MOD1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.428504782
Minimum0
Maximum9
Zeros11659
Zeros (%)27.2%
Memory size334.8 KiB
2020-11-30T23:58:17.560013image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.465377198
Coefficient of variation (CV)1.025811895
Kurtosis5.756624515
Mean1.428504782
Median Absolute Deviation (MAD)1
Skewness1.67000392
Sum48992
Variance2.147330332
MonotocityNot monotonic
2020-11-30T23:58:17.637425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
01165927.2%
 
2857920.0%
 
1734517.1%
 
342139.8%
 
421305.0%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
01165927.2%
 
1734517.1%
 
2857920.0%
 
342139.8%
 
421305.0%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
421305.0%
 
342139.8%
 
2857920.0%
 
1734517.1%
 
01165927.2%
 

KBA05_MOD2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.064934686
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:17.716777image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.173657385
Coefficient of variation (CV)0.3829306346
Kurtosis5.490248678
Mean3.064934686
Median Absolute Deviation (MAD)1
Skewness1.261435445
Sum105115
Variance1.377471656
MonotocityNot monotonic
2020-11-30T23:58:17.798742image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31440533.6%
 
4747017.4%
 
2720316.8%
 
124895.8%
 
523595.5%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
124895.8%
 
2720316.8%
 
31440533.6%
 
4747017.4%
 
523595.5%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
523595.5%
 
4747017.4%
 
31440533.6%
 
2720316.8%
 
124895.8%
 

KBA05_MOD3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.084178913
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:17.889688image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.196485784
Coefficient of variation (CV)0.3879430533
Kurtosis4.833969257
Mean3.084178913
Median Absolute Deviation (MAD)1
Skewness1.181255308
Sum105775
Variance1.431578232
MonotocityNot monotonic
2020-11-30T23:58:17.972522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31301830.4%
 
4806618.8%
 
2780518.2%
 
526206.1%
 
124175.6%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
124175.6%
 
2780518.2%
 
31301830.4%
 
4806618.8%
 
526206.1%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
526206.1%
 
4806618.8%
 
31301830.4%
 
2780518.2%
 
124175.6%
 

KBA05_MOD4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.780586657
Minimum0
Maximum9
Zeros1719
Zeros (%)4.0%
Memory size334.8 KiB
2020-11-30T23:58:18.062825image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.446463223
Coefficient of variation (CV)0.5202007352
Kurtosis2.295858975
Mean2.780586657
Median Absolute Deviation (MAD)1
Skewness0.6526535471
Sum95363
Variance2.092255856
MonotocityNot monotonic
2020-11-30T23:58:18.138400image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31082825.3%
 
2764817.9%
 
4598614.0%
 
1460410.7%
 
531417.3%
 
017194.0%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
017194.0%
 
1460410.7%
 
2764817.9%
 
31082825.3%
 
4598614.0%
 
531417.3%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
531417.3%
 
4598614.0%
 
31082825.3%
 
2764817.9%
 
1460410.7%
 
017194.0%
 

KBA05_MOD8
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.362403779
Minimum0
Maximum9
Zeros8550
Zeros (%)20.0%
Memory size334.8 KiB
2020-11-30T23:58:18.216680image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.247580349
Coefficient of variation (CV)0.9157199709
Kurtosis12.86432112
Mean1.362403779
Median Absolute Deviation (MAD)1
Skewness2.434959405
Sum46725
Variance1.556456726
MonotocityNot monotonic
2020-11-30T23:58:18.292754image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11117426.1%
 
21038524.2%
 
0855020.0%
 
338178.9%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
0855020.0%
 
11117426.1%
 
21038524.2%
 
338178.9%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
338178.9%
 
21038524.2%
 
11117426.1%
 
0855020.0%
 

KBA05_MODTEMP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean2.920070443
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:18.371566image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.197107225
Coefficient of variation (CV)0.4099583377
Kurtosis-0.6576535512
Mean2.920070443
Median Absolute Deviation (MAD)1
Skewness-0.2206325812
Sum102804
Variance1.433065707
MonotocityNot monotonic
2020-11-30T23:58:18.455282image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31270529.7%
 
4993223.2%
 
1678415.8%
 
236848.6%
 
517974.2%
 
63040.7%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
1678415.8%
 
236848.6%
 
31270529.7%
 
4993223.2%
 
517974.2%
 
63040.7%
 
ValueCountFrequency (%) 
63040.7%
 
517974.2%
 
4993223.2%
 
31270529.7%
 
236848.6%
 
1678415.8%
 

KBA05_MOTOR
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.637304642
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:18.535778image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.132012832
Coefficient of variation (CV)0.429230971
Kurtosis8.754123989
Mean2.637304642
Median Absolute Deviation (MAD)1
Skewness1.718764226
Sum90449
Variance1.281453053
MonotocityNot monotonic
2020-11-30T23:58:18.617062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31339431.3%
 
21029224.0%
 
4537112.5%
 
1486911.4%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
1486911.4%
 
21029224.0%
 
31339431.3%
 
4537112.5%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
4537112.5%
 
31339431.3%
 
21029224.0%
 
1486911.4%
 

KBA05_MOTRAD
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.194016795
Minimum0
Maximum9
Zeros8115
Zeros (%)18.9%
Memory size334.8 KiB
2020-11-30T23:58:18.706599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q31
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.189728753
Coefficient of variation (CV)0.9964087253
Kurtosis15.95367284
Mean1.194016795
Median Absolute Deviation (MAD)0
Skewness2.964919255
Sum40950
Variance1.415454505
MonotocityNot monotonic
2020-11-30T23:58:18.779128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11787341.7%
 
0811518.9%
 
341239.6%
 
238519.0%
 
93340.8%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
0811518.9%
 
11787341.7%
 
238519.0%
 
341239.6%
 
93340.8%
 
ValueCountFrequency (%) 
93340.8%
 
341239.6%
 
238519.0%
 
11787341.7%
 
0811518.9%
 

KBA05_SEG1
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.170486354
Minimum0
Maximum9
Zeros10315
Zeros (%)24.1%
Memory size334.8 KiB
2020-11-30T23:58:18.856771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.218511137
Coefficient of variation (CV)1.041029768
Kurtosis16.05256257
Mean1.170486354
Median Absolute Deviation (MAD)1
Skewness2.905613443
Sum40143
Variance1.484769392
MonotocityNot monotonic
2020-11-30T23:58:18.931741image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11276929.8%
 
01031524.1%
 
2848219.8%
 
323605.5%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
01031524.1%
 
11276929.8%
 
2848219.8%
 
323605.5%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
323605.5%
 
2848219.8%
 
11276929.8%
 
01031524.1%
 

KBA05_SEG10
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.990202939
Minimum0
Maximum9
Zeros3992
Zeros (%)9.3%
Memory size334.8 KiB
2020-11-30T23:58:19.008864image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.313501703
Coefficient of variation (CV)0.6599838022
Kurtosis6.936360048
Mean1.990202939
Median Absolute Deviation (MAD)1
Skewness1.517250124
Sum68256
Variance1.725286724
MonotocityNot monotonic
2020-11-30T23:58:19.084309image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21293030.2%
 
1731817.1%
 
3699616.3%
 
039929.3%
 
426906.3%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
039929.3%
 
1731817.1%
 
21293030.2%
 
3699616.3%
 
426906.3%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
426906.3%
 
3699616.3%
 
21293030.2%
 
1731817.1%
 
039929.3%
 

KBA05_SEG2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.0252216
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:19.163389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.180553705
Coefficient of variation (CV)0.3902371004
Kurtosis5.502123008
Mean3.0252216
Median Absolute Deviation (MAD)1
Skewness1.258331075
Sum103753
Variance1.393707051
MonotocityNot monotonic
2020-11-30T23:58:19.245724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31433133.5%
 
2733317.1%
 
4729417.0%
 
128136.6%
 
521555.0%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
128136.6%
 
2733317.1%
 
31433133.5%
 
4729417.0%
 
521555.0%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
521555.0%
 
4729417.0%
 
31433133.5%
 
2733317.1%
 
128136.6%
 

KBA05_SEG3
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.063564264
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:19.335272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.198670473
Coefficient of variation (CV)0.3912666325
Kurtosis4.865825091
Mean3.063564264
Median Absolute Deviation (MAD)1
Skewness1.220061314
Sum105068
Variance1.436810903
MonotocityNot monotonic
2020-11-30T23:58:19.416812image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31301230.4%
 
2821119.2%
 
4764317.8%
 
526626.2%
 
123985.6%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
123985.6%
 
2821119.2%
 
31301230.4%
 
4764317.8%
 
526626.2%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
526626.2%
 
4764317.8%
 
31301230.4%
 
2821119.2%
 
123985.6%
 

KBA05_SEG4
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.085286914
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:19.518430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.166819493
Coefficient of variation (CV)0.3781883259
Kurtosis5.616058521
Mean3.085286914
Median Absolute Deviation (MAD)1
Skewness1.292998032
Sum105813
Variance1.361467729
MonotocityNot monotonic
2020-11-30T23:58:19.603774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31544636.1%
 
4677215.8%
 
2666115.6%
 
526726.2%
 
123755.5%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
123755.5%
 
2666115.6%
 
31544636.1%
 
4677215.8%
 
526726.2%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
526726.2%
 
4677215.8%
 
31544636.1%
 
2666115.6%
 
123755.5%
 

KBA05_SEG5
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.572253324
Minimum0
Maximum9
Zeros7113
Zeros (%)16.6%
Memory size334.8 KiB
2020-11-30T23:58:19.696571image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q32
95-th percentile4
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.377542117
Coefficient of variation (CV)0.8761578661
Kurtosis7.25033312
Mean1.572253324
Median Absolute Deviation (MAD)1
Skewness1.856682746
Sum53922
Variance1.897622285
MonotocityNot monotonic
2020-11-30T23:58:19.773522image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11169127.3%
 
2867720.3%
 
0711316.6%
 
342339.9%
 
422125.2%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
0711316.6%
 
11169127.3%
 
2867720.3%
 
342339.9%
 
422125.2%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
422125.2%
 
342339.9%
 
2867720.3%
 
11169127.3%
 
0711316.6%
 

KBA05_SEG6
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Memory size334.8 KiB
0
29440 
1
4486 
9
 
370
ValueCountFrequency (%) 
02944068.7%
 
1448610.5%
 
93700.9%
 
(Missing)853719.9%
 
2020-11-30T23:58:19.872302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
06373649.6%
 
.3429626.7%
 
n1707413.3%
 
a85376.6%
 
144863.5%
 
93700.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6859253.4%
 
Other Punctuation3429626.7%
 
Lowercase Letter2561119.9%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
06373692.9%
 
144866.5%
 
93700.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34296100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10288880.1%
 
Latin2561119.9%
 

Most frequent Common characters

ValueCountFrequency (%) 
06373661.9%
 
.3429633.3%
 
144864.4%
 
93700.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1707466.7%
 
a853733.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
06373649.6%
 
.3429626.7%
 
n1707413.3%
 
a85376.6%
 
144863.5%
 
93700.3%
 

KBA05_SEG7
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean0.9673722883
Minimum0
Maximum9
Zeros15140
Zeros (%)35.3%
Memory size334.8 KiB
2020-11-30T23:58:19.964974image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.255847841
Coefficient of variation (CV)1.29820531
Kurtosis15.73124428
Mean0.9673722883
Median Absolute Deviation (MAD)1
Skewness2.99440082
Sum33177
Variance1.577153801
MonotocityNot monotonic
2020-11-30T23:58:20.038243image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
01514035.3%
 
1984723.0%
 
2681715.9%
 
321225.0%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
01514035.3%
 
1984723.0%
 
2681715.9%
 
321225.0%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
321225.0%
 
2681715.9%
 
1984723.0%
 
01514035.3%
 

KBA05_SEG8
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean0.8500116632
Minimum0
Maximum9
Zeros17271
Zeros (%)40.3%
Memory size334.8 KiB
2020-11-30T23:58:20.116311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.24235478
Coefficient of variation (CV)1.461573804
Kurtosis17.68313744
Mean0.8500116632
Median Absolute Deviation (MAD)0
Skewness3.285236255
Sum29152
Variance1.5434454
MonotocityNot monotonic
2020-11-30T23:58:20.188650image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
01727140.3%
 
1928121.7%
 
2558113.0%
 
317934.2%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
01727140.3%
 
1928121.7%
 
2558113.0%
 
317934.2%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
317934.2%
 
2558113.0%
 
1928121.7%
 
01727140.3%
 

KBA05_SEG9
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean1.179700257
Minimum0
Maximum9
Zeros10277
Zeros (%)24.0%
Memory size334.8 KiB
2020-11-30T23:58:20.266252image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile3
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.219531808
Coefficient of variation (CV)1.033764129
Kurtosis15.89936337
Mean1.179700257
Median Absolute Deviation (MAD)1
Skewness2.877446059
Sum40459
Variance1.487257831
MonotocityNot monotonic
2020-11-30T23:58:20.337201image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11250729.2%
 
01027724.0%
 
2880420.6%
 
323385.5%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
01027724.0%
 
11250729.2%
 
2880420.6%
 
323385.5%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
323385.5%
 
2880420.6%
 
11250729.2%
 
01027724.0%
 

KBA05_VORB0
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.13648822
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:20.413302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.248834986
Coefficient of variation (CV)0.3981634548
Kurtosis3.652131245
Mean3.13648822
Median Absolute Deviation (MAD)1
Skewness0.9471446189
Sum107569
Variance1.559588822
MonotocityNot monotonic
2020-11-30T23:58:20.497415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31187727.7%
 
4865120.2%
 
2714616.7%
 
533657.9%
 
128876.7%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
128876.7%
 
2714616.7%
 
31187727.7%
 
4865120.2%
 
533657.9%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
533657.9%
 
4865120.2%
 
31187727.7%
 
2714616.7%
 
128876.7%
 

KBA05_VORB1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.063331001
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:20.584710image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.187980396
Coefficient of variation (CV)0.3878067358
Kurtosis5.192934593
Mean3.063331001
Median Absolute Deviation (MAD)1
Skewness1.232437893
Sum105060
Variance1.411297421
MonotocityNot monotonic
2020-11-30T23:58:20.667101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31469234.3%
 
2700916.4%
 
4689716.1%
 
526806.3%
 
126486.2%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
126486.2%
 
2700916.4%
 
31469234.3%
 
4689716.1%
 
526806.3%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
526806.3%
 
4689716.1%
 
31469234.3%
 
2700916.4%
 
126486.2%
 

KBA05_VORB2
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.530440868
Minimum0
Maximum9
Zeros2710
Zeros (%)6.3%
Memory size334.8 KiB
2020-11-30T23:58:20.758149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.449265639
Coefficient of variation (CV)0.5727324662
Kurtosis2.868850477
Mean2.530440868
Median Absolute Deviation (MAD)1
Skewness0.8008686485
Sum86784
Variance2.100370892
MonotocityNot monotonic
2020-11-30T23:58:24.878521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31104025.8%
 
2857120.0%
 
1511611.9%
 
4436910.2%
 
027106.3%
 
521204.9%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
027106.3%
 
1511611.9%
 
2857120.0%
 
31104025.8%
 
4436910.2%
 
521204.9%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
521204.9%
 
4436910.2%
 
31104025.8%
 
2857120.0%
 
1511611.9%
 
027106.3%
 

KBA05_ZUL1
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.926696991
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:24.962419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.168744387
Coefficient of variation (CV)0.3993390469
Kurtosis6.248795067
Mean2.926696991
Median Absolute Deviation (MAD)1
Skewness1.380251863
Sum100374
Variance1.365963442
MonotocityNot monotonic
2020-11-30T23:58:25.064237image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31468234.3%
 
2792218.5%
 
4650015.2%
 
132397.6%
 
515833.7%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
132397.6%
 
2792218.5%
 
31468234.3%
 
4650015.2%
 
515833.7%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
515833.7%
 
4650015.2%
 
31468234.3%
 
2792218.5%
 
132397.6%
 

KBA05_ZUL2
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.10902146
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:25.159914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.176795731
Coefficient of variation (CV)0.3785100058
Kurtosis5.197516386
Mean3.10902146
Median Absolute Deviation (MAD)1
Skewness1.241066794
Sum106627
Variance1.384848192
MonotocityNot monotonic
2020-11-30T23:58:25.242589image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31400032.7%
 
4769718.0%
 
2734417.1%
 
527346.4%
 
121515.0%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
121515.0%
 
2734417.1%
 
31400032.7%
 
4769718.0%
 
527346.4%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
527346.4%
 
4769718.0%
 
31400032.7%
 
2734417.1%
 
121515.0%
 

KBA05_ZUL3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.866427572
Minimum0
Maximum9
Zeros1971
Zeros (%)4.6%
Memory size334.8 KiB
2020-11-30T23:58:25.336545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.413915644
Coefficient of variation (CV)0.4932675286
Kurtosis2.583087068
Mean2.866427572
Median Absolute Deviation (MAD)1
Skewness0.5132602577
Sum98307
Variance1.999157449
MonotocityNot monotonic
2020-11-30T23:58:25.411802image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31099825.7%
 
4777818.2%
 
2746017.4%
 
131617.4%
 
525586.0%
 
019714.6%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
019714.6%
 
131617.4%
 
2746017.4%
 
31099825.7%
 
4777818.2%
 
525586.0%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
525586.0%
 
4777818.2%
 
31099825.7%
 
2746017.4%
 
131617.4%
 
019714.6%
 

KBA05_ZUL4
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean2.315226265
Minimum0
Maximum9
Zeros3327
Zeros (%)7.8%
Memory size334.8 KiB
2020-11-30T23:58:25.491291image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.557669079
Coefficient of variation (CV)0.6727934553
Kurtosis2.058389811
Mean2.315226265
Median Absolute Deviation (MAD)1
Skewness0.9340008228
Sum79403
Variance2.426332959
MonotocityNot monotonic
2020-11-30T23:58:25.567588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
2896720.9%
 
1819719.1%
 
3611714.3%
 
4499911.7%
 
033277.8%
 
523195.4%
 
93700.9%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
033277.8%
 
1819719.1%
 
2896720.9%
 
3611714.3%
 
4499911.7%
 
523195.4%
 
93700.9%
 
ValueCountFrequency (%) 
93700.9%
 
523195.4%
 
4499911.7%
 
3611714.3%
 
2896720.9%
 
1819719.1%
 
033277.8%
 

KBA13_ALTERHALTER_30
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.901691815
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:25.647626image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.061184713
Coefficient of variation (CV)0.3657124123
Kurtosis-0.395259949
Mean2.901691815
Median Absolute Deviation (MAD)1
Skewness0.03200968508
Sum101536
Variance1.126112996
MonotocityNot monotonic
2020-11-30T23:58:25.732631image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31464834.2%
 
2751317.5%
 
4636514.9%
 
138068.9%
 
526606.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
138068.9%
 
2751317.5%
 
31464834.2%
 
4636514.9%
 
526606.2%
 
ValueCountFrequency (%) 
526606.2%
 
4636514.9%
 
31464834.2%
 
2751317.5%
 
138068.9%
 

KBA13_ALTERHALTER_45
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.998571102
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:25.825599image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.096341269
Coefficient of variation (CV)0.3656212348
Kurtosis-0.5164091918
Mean2.998571102
Median Absolute Deviation (MAD)1
Skewness0.00295592781
Sum104926
Variance1.201964178
MonotocityNot monotonic
2020-11-30T23:58:25.913311image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31380532.2%
 
2714116.7%
 
4708916.6%
 
534798.1%
 
134788.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
134788.1%
 
2714116.7%
 
31380532.2%
 
4708916.6%
 
534798.1%
 
ValueCountFrequency (%) 
534798.1%
 
4708916.6%
 
31380532.2%
 
2714116.7%
 
134788.1%
 

KBA13_ALTERHALTER_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.90849337
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:26.005444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.068152802
Coefficient of variation (CV)0.3672529611
Kurtosis-0.4474454322
Mean2.90849337
Median Absolute Deviation (MAD)1
Skewness0.07491467364
Sum101774
Variance1.140950409
MonotocityNot monotonic
2020-11-30T23:58:26.090339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31399732.7%
 
2813019.0%
 
4645815.1%
 
135868.4%
 
528216.6%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
135868.4%
 
2813019.0%
 
31399732.7%
 
4645815.1%
 
528216.6%
 
ValueCountFrequency (%) 
528216.6%
 
4645815.1%
 
31399732.7%
 
2813019.0%
 
135868.4%
 

KBA13_ALTERHALTER_61
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.14546182
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:26.191858image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.083330338
Coefficient of variation (CV)0.3444105828
Kurtosis-0.4998328371
Mean3.14546182
Median Absolute Deviation (MAD)1
Skewness-0.04334331945
Sum110066
Variance1.173604622
MonotocityNot monotonic
2020-11-30T23:58:26.292793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31388332.4%
 
4781518.2%
 
2639514.9%
 
5436710.2%
 
125325.9%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
125325.9%
 
2639514.9%
 
31388332.4%
 
4781518.2%
 
5436710.2%
 
ValueCountFrequency (%) 
5436710.2%
 
4781518.2%
 
31388332.4%
 
2639514.9%
 
125325.9%
 

KBA13_ANTG1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.279120942
Minimum0
Maximum4
Zeros364
Zeros (%)0.8%
Memory size334.8 KiB
2020-11-30T23:58:26.386536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.931276102
Coefficient of variation (CV)0.4086119718
Kurtosis-0.6587938538
Mean2.279120942
Median Absolute Deviation (MAD)1
Skewness0.05579557577
Sum79751
Variance0.8672751782
MonotocityNot monotonic
2020-11-30T23:58:26.469399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21309430.6%
 
31097325.6%
 
1720016.8%
 
433617.8%
 
03640.8%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
03640.8%
 
1720016.8%
 
21309430.6%
 
31097325.6%
 
433617.8%
 
ValueCountFrequency (%) 
433617.8%
 
31097325.6%
 
21309430.6%
 
1720016.8%
 
03640.8%
 

KBA13_ANTG2
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.686356882
Minimum0
Maximum4
Zeros501
Zeros (%)1.2%
Memory size334.8 KiB
2020-11-30T23:58:26.559556image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9337269927
Coefficient of variation (CV)0.347581142
Kurtosis-0.2123078921
Mean2.686356882
Median Absolute Deviation (MAD)1
Skewness-0.4187937579
Sum94001
Variance0.8718460969
MonotocityNot monotonic
2020-11-30T23:58:26.643280image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31440833.6%
 
21009923.6%
 
4686516.0%
 
131197.3%
 
05011.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
05011.2%
 
131197.3%
 
21009923.6%
 
31440833.6%
 
4686516.0%
 
ValueCountFrequency (%) 
4686516.0%
 
31440833.6%
 
21009923.6%
 
131197.3%
 
05011.2%
 

KBA13_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
1
10654 
2
10417 
0
7226 
3
6695 
ValueCountFrequency (%) 
11065424.9%
 
21041724.3%
 
0722616.9%
 
3669515.6%
 
(Missing)784118.3%
 
2020-11-30T23:58:26.754577image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
04221832.9%
 
.3499227.2%
 
n1568212.2%
 
1106548.3%
 
2104178.1%
 
a78416.1%
 
366955.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
04221860.3%
 
11065415.2%
 
21041714.9%
 
366959.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
04221840.2%
 
.3499233.3%
 
11065410.1%
 
2104179.9%
 
366956.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
04221832.9%
 
.3499227.2%
 
n1568212.2%
 
1106548.3%
 
2104178.1%
 
a78416.1%
 
366955.2%
 

KBA13_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
0
19008 
1
11224 
2
4760 
ValueCountFrequency (%) 
01900844.4%
 
11122426.2%
 
2476011.1%
 
(Missing)784118.3%
 
2020-11-30T23:58:26.861380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
05400042.0%
 
.3499227.2%
 
n1568212.2%
 
1112248.7%
 
a78416.1%
 
247603.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
05400077.2%
 
11122416.0%
 
247606.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
05400051.4%
 
.3499233.3%
 
11122410.7%
 
247604.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
05400042.0%
 
.3499227.2%
 
n1568212.2%
 
1112248.7%
 
a78416.1%
 
247603.7%
 

KBA13_ANZAHL_PKW
Real number (ℝ≥0)

MISSING

Distinct1231
Distinct (%)3.5%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean618.5086591
Minimum0
Maximum2300
Zeros1
Zeros (%)< 0.1%
Memory size334.8 KiB
2020-11-30T23:58:26.966643image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile208
Q1388
median549
Q3771
95-th percentile1300
Maximum2300
Range2300
Interquartile range (IQR)383

Descriptive statistics

Standard deviation332.8799188
Coefficient of variation (CV)0.5381976694
Kurtosis2.115788847
Mean618.5086591
Median Absolute Deviation (MAD)184
Skewness1.283531289
Sum21642855
Variance110809.0404
MonotocityNot monotonic
2020-11-30T23:58:27.084284image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
14005071.2%
 
15003380.8%
 
16002940.7%
 
13002760.6%
 
17001620.4%
 
18001190.3%
 
526810.2%
 
584790.2%
 
396760.2%
 
485740.2%
 
589730.2%
 
430730.2%
 
402720.2%
 
487720.2%
 
536710.2%
 
417700.2%
 
451700.2%
 
494700.2%
 
492700.2%
 
386690.2%
 
568680.2%
 
445670.2%
 
369670.2%
 
534670.2%
 
345670.2%
 
Other values (1206)3194074.6%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
01< 0.1%
 
42< 0.1%
 
142< 0.1%
 
161< 0.1%
 
211< 0.1%
 
221< 0.1%
 
233< 0.1%
 
241< 0.1%
 
311< 0.1%
 
321< 0.1%
 
ValueCountFrequency (%) 
230013< 0.1%
 
220012< 0.1%
 
2100250.1%
 
2000630.1%
 
1900520.1%
 
18001190.3%
 
17001620.4%
 
16002940.7%
 
15003380.8%
 
14005071.2%
 

KBA13_AUDI
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.089934842
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:27.181606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.011465452
Coefficient of variation (CV)0.3273420002
Kurtosis-0.2796649336
Mean3.089934842
Median Absolute Deviation (MAD)1
Skewness-0.01284055364
Sum108123
Variance1.02306236
MonotocityNot monotonic
2020-11-30T23:58:27.266211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31518935.5%
 
4775018.1%
 
2662715.5%
 
532197.5%
 
122075.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122075.2%
 
2662715.5%
 
31518935.5%
 
4775018.1%
 
532197.5%
 
ValueCountFrequency (%) 
532197.5%
 
4775018.1%
 
31518935.5%
 
2662715.5%
 
122075.2%
 

KBA13_AUTOQUOTE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.925325789
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:27.358438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.043697822
Coefficient of variation (CV)0.3567800298
Kurtosis-0.389965339
Mean2.925325789
Median Absolute Deviation (MAD)1
Skewness0.04827624758
Sum102363
Variance1.089305144
MonotocityNot monotonic
2020-11-30T23:58:27.442836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31436933.5%
 
2800018.7%
 
4672715.7%
 
132837.7%
 
526136.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
132837.7%
 
2800018.7%
 
31436933.5%
 
4672715.7%
 
526136.1%
 
ValueCountFrequency (%) 
526136.1%
 
4672715.7%
 
31436933.5%
 
2800018.7%
 
132837.7%
 

KBA13_BAUMAX
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean1.854223823
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:27.534728image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.416327742
Coefficient of variation (CV)0.7638386073
Kurtosis0.267548827
Mean1.854223823
Median Absolute Deviation (MAD)0
Skewness1.368055249
Sum64883
Variance2.005984274
MonotocityNot monotonic
2020-11-30T23:58:27.615180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
12372755.4%
 
540919.6%
 
228396.6%
 
323175.4%
 
420184.7%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
12372755.4%
 
228396.6%
 
323175.4%
 
420184.7%
 
540919.6%
 
ValueCountFrequency (%) 
540919.6%
 
420184.7%
 
323175.4%
 
228396.6%
 
12372755.4%
 

KBA13_BJ_1999
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.9027492
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:27.703914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9594692098
Coefficient of variation (CV)0.3305381015
Kurtosis-0.1177396286
Mean2.9027492
Median Absolute Deviation (MAD)1
Skewness0.03951272094
Sum101573
Variance0.9205811645
MonotocityNot monotonic
2020-11-30T23:58:27.793192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31601837.4%
 
2812619.0%
 
4632514.8%
 
126626.2%
 
518614.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
126626.2%
 
2812619.0%
 
31601837.4%
 
4632514.8%
 
518614.3%
 
ValueCountFrequency (%) 
518614.3%
 
4632514.8%
 
31601837.4%
 
2812619.0%
 
126626.2%
 

KBA13_BJ_2000
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.852909236
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:27.888385image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9719557033
Coefficient of variation (CV)0.3406893184
Kurtosis-0.1675320973
Mean2.852909236
Median Absolute Deviation (MAD)1
Skewness0.02387464684
Sum99829
Variance0.9446978892
MonotocityNot monotonic
2020-11-30T23:58:27.981505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31580136.9%
 
2826819.3%
 
4604914.1%
 
131697.4%
 
517054.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
131697.4%
 
2826819.3%
 
31580136.9%
 
4604914.1%
 
517054.0%
 
ValueCountFrequency (%) 
517054.0%
 
4604914.1%
 
31580136.9%
 
2826819.3%
 
131697.4%
 

KBA13_BJ_2004
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.028749428
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:28.078244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9470729433
Coefficient of variation (CV)0.3126943861
Kurtosis-0.07039941524
Mean3.028749428
Median Absolute Deviation (MAD)1
Skewness0.0101694605
Sum105982
Variance0.89694716
MonotocityNot monotonic
2020-11-30T23:58:28.164696image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31638838.3%
 
4733617.1%
 
2699816.3%
 
523025.4%
 
119684.6%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
119684.6%
 
2699816.3%
 
31638838.3%
 
4733617.1%
 
523025.4%
 
ValueCountFrequency (%) 
523025.4%
 
4733617.1%
 
31638838.3%
 
2699816.3%
 
119684.6%
 

KBA13_BJ_2006
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.074988569
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:28.260243image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9458976462
Coefficient of variation (CV)0.3076101342
Kurtosis-0.09709509091
Mean3.074988569
Median Absolute Deviation (MAD)1
Skewness0.0008169524668
Sum107600
Variance0.894722357
MonotocityNot monotonic
2020-11-30T23:58:28.346952image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31620537.8%
 
4784318.3%
 
2670515.7%
 
524915.8%
 
117484.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
117484.1%
 
2670515.7%
 
31620537.8%
 
4784318.3%
 
524915.8%
 
ValueCountFrequency (%) 
524915.8%
 
4784318.3%
 
31620537.8%
 
2670515.7%
 
117484.1%
 

KBA13_BJ_2008
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.533893461
Minimum0
Maximum5
Zeros5495
Zeros (%)12.8%
Memory size334.8 KiB
2020-11-30T23:58:28.436819image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.474578601
Coefficient of variation (CV)0.5819418313
Kurtosis-0.6281747926
Mean2.533893461
Median Absolute Deviation (MAD)1
Skewness-0.2709012458
Sum88666
Variance2.174382051
MonotocityNot monotonic
2020-11-30T23:58:28.519857image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31289730.1%
 
2658515.4%
 
0549512.8%
 
441389.7%
 
535948.4%
 
122835.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0549512.8%
 
122835.3%
 
2658515.4%
 
31289730.1%
 
441389.7%
 
535948.4%
 
ValueCountFrequency (%) 
535948.4%
 
441389.7%
 
31289730.1%
 
2658515.4%
 
122835.3%
 
0549512.8%
 

KBA13_BJ_2009
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.562985825
Minimum0
Maximum5
Zeros4165
Zeros (%)9.7%
Memory size334.8 KiB
2020-11-30T23:58:28.598273image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.455199915
Coefficient of variation (CV)0.5677752488
Kurtosis-0.7093423818
Mean2.562985825
Median Absolute Deviation (MAD)1
Skewness-0.1951117671
Sum89684
Variance2.117606791
MonotocityNot monotonic
2020-11-30T23:58:28.681458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31295730.3%
 
2512112.0%
 
1472511.0%
 
4427410.0%
 
041659.7%
 
537508.8%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
041659.7%
 
1472511.0%
 
2512112.0%
 
31295730.3%
 
4427410.0%
 
537508.8%
 
ValueCountFrequency (%) 
537508.8%
 
4427410.0%
 
31295730.3%
 
2512112.0%
 
1472511.0%
 
041659.7%
 

KBA13_BMW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.193444216
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:28.763451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.01760076
Coefficient of variation (CV)0.3186530563
Kurtosis-0.3519512858
Mean3.193444216
Median Absolute Deviation (MAD)1
Skewness-0.01491292242
Sum111745
Variance1.035511306
MonotocityNot monotonic
2020-11-30T23:58:28.848875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31484034.6%
 
4823519.2%
 
2612014.3%
 
540629.5%
 
117354.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
117354.1%
 
2612014.3%
 
31484034.6%
 
4823519.2%
 
540629.5%
 
ValueCountFrequency (%) 
540629.5%
 
4823519.2%
 
31484034.6%
 
2612014.3%
 
117354.1%
 

KBA13_CCM_0_1400
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.268661408
Minimum0
Maximum5
Zeros6437
Zeros (%)15.0%
Memory size334.8 KiB
2020-11-30T23:58:28.940190image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.435806075
Coefficient of variation (CV)0.6328868951
Kurtosis-0.6891547329
Mean2.268661408
Median Absolute Deviation (MAD)1
Skewness-0.108698181
Sum79385
Variance2.061539084
MonotocityNot monotonic
2020-11-30T23:58:29.028286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31157327.0%
 
2845319.7%
 
0643715.0%
 
432177.5%
 
129176.8%
 
523955.6%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0643715.0%
 
129176.8%
 
2845319.7%
 
31157327.0%
 
432177.5%
 
523955.6%
 
ValueCountFrequency (%) 
523955.6%
 
432177.5%
 
31157327.0%
 
2845319.7%
 
129176.8%
 
0643715.0%
 

KBA13_CCM_1000
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.37345679
Minimum0
Maximum5
Zeros4466
Zeros (%)10.4%
Memory size334.8 KiB
2020-11-30T23:58:29.113703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.411074432
Coefficient of variation (CV)0.5945229076
Kurtosis-0.718680166
Mean2.37345679
Median Absolute Deviation (MAD)1
Skewness-0.08278885049
Sum83052
Variance1.991131053
MonotocityNot monotonic
2020-11-30T23:58:29.204944image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31265929.6%
 
2587313.7%
 
1577413.5%
 
0446610.4%
 
435458.3%
 
526756.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0446610.4%
 
1577413.5%
 
2587313.7%
 
31265929.6%
 
435458.3%
 
526756.2%
 
ValueCountFrequency (%) 
526756.2%
 
435458.3%
 
31265929.6%
 
2587313.7%
 
1577413.5%
 
0446610.4%
 

KBA13_CCM_1200
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.267575446
Minimum0
Maximum5
Zeros6755
Zeros (%)15.8%
Memory size334.8 KiB
2020-11-30T23:58:29.289073image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.458226211
Coefficient of variation (CV)0.643077263
Kurtosis-0.7772386275
Mean2.267575446
Median Absolute Deviation (MAD)1
Skewness-0.1353139324
Sum79347
Variance2.126423683
MonotocityNot monotonic
2020-11-30T23:58:29.377642image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31202828.1%
 
2739617.3%
 
0675515.8%
 
434228.0%
 
130437.1%
 
523485.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0675515.8%
 
130437.1%
 
2739617.3%
 
31202828.1%
 
434228.0%
 
523485.5%
 
ValueCountFrequency (%) 
523485.5%
 
434228.0%
 
31202828.1%
 
2739617.3%
 
130437.1%
 
0675515.8%
 

KBA13_CCM_1400
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.976851852
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:29.460375image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9505394217
Coefficient of variation (CV)0.3193102878
Kurtosis-0.1039848903
Mean2.976851852
Median Absolute Deviation (MAD)1
Skewness0.05390838593
Sum104166
Variance0.9035251922
MonotocityNot monotonic
2020-11-30T23:58:29.546306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31611737.6%
 
2775518.1%
 
4686716.0%
 
521465.0%
 
121074.9%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
121074.9%
 
2775518.1%
 
31611737.6%
 
4686716.0%
 
521465.0%
 
ValueCountFrequency (%) 
521465.0%
 
4686716.0%
 
31611737.6%
 
2775518.1%
 
121074.9%
 

KBA13_CCM_1401_2500
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.968649977
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:29.639208image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9490554008
Coefficient of variation (CV)0.3196925903
Kurtosis-0.1219334791
Mean2.968649977
Median Absolute Deviation (MAD)1
Skewness-0.1118642957
Sum103879
Variance0.9007061537
MonotocityNot monotonic
2020-11-30T23:58:29.725063image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31612837.7%
 
4763817.8%
 
2699716.3%
 
125496.0%
 
516803.9%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
125496.0%
 
2699716.3%
 
31612837.7%
 
4763817.8%
 
516803.9%
 
ValueCountFrequency (%) 
516803.9%
 
4763817.8%
 
31612837.7%
 
2699716.3%
 
125496.0%
 

KBA13_CCM_1500
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.632601738
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:29.817420image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.420994631
Coefficient of variation (CV)0.5397681734
Kurtosis-1.443821038
Mean2.632601738
Median Absolute Deviation (MAD)1
Skewness0.09877652081
Sum92120
Variance2.019225742
MonotocityNot monotonic
2020-11-30T23:58:29.901521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11265029.5%
 
4908021.2%
 
3709516.6%
 
531777.4%
 
229907.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
11265029.5%
 
229907.0%
 
3709516.6%
 
4908021.2%
 
531777.4%
 
ValueCountFrequency (%) 
531777.4%
 
4908021.2%
 
3709516.6%
 
229907.0%
 
11265029.5%
 

KBA13_CCM_1600
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.033550526
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:29.995416image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9482420449
Coefficient of variation (CV)0.3125848859
Kurtosis-0.1126934868
Mean3.033550526
Median Absolute Deviation (MAD)1
Skewness0.06650194457
Sum106150
Variance0.8991629757
MonotocityNot monotonic
2020-11-30T23:58:30.081183image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31615337.7%
 
2738517.2%
 
4723316.9%
 
524425.7%
 
117794.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
117794.2%
 
2738517.2%
 
31615337.7%
 
4723316.9%
 
524425.7%
 
ValueCountFrequency (%) 
524425.7%
 
4723316.9%
 
31615337.7%
 
2738517.2%
 
117794.2%
 

KBA13_CCM_1800
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.405006859
Minimum0
Maximum5
Zeros5935
Zeros (%)13.9%
Memory size334.8 KiB
2020-11-30T23:58:30.170645image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.444269623
Coefficient of variation (CV)0.6005261971
Kurtosis-0.6348595458
Mean2.405006859
Median Absolute Deviation (MAD)1
Skewness-0.217087042
Sum84156
Variance2.085914744
MonotocityNot monotonic
2020-11-30T23:58:30.253929image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31240829.0%
 
2773418.1%
 
0593513.9%
 
438118.9%
 
527796.5%
 
123255.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0593513.9%
 
123255.4%
 
2773418.1%
 
31240829.0%
 
438118.9%
 
527796.5%
 
ValueCountFrequency (%) 
527796.5%
 
438118.9%
 
31240829.0%
 
2773418.1%
 
123255.4%
 
0593513.9%
 

KBA13_CCM_2000
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.117912666
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:30.337163image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9488578897
Coefficient of variation (CV)0.304324717
Kurtosis-0.1613280676
Mean3.117912666
Median Absolute Deviation (MAD)1
Skewness0.04190786044
Sum109102
Variance0.9003312949
MonotocityNot monotonic
2020-11-30T23:58:30.423070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31593837.2%
 
4804618.8%
 
2669615.6%
 
528506.7%
 
114623.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
114623.4%
 
2669615.6%
 
31593837.2%
 
4804618.8%
 
528506.7%
 
ValueCountFrequency (%) 
528506.7%
 
4804618.8%
 
31593837.2%
 
2669615.6%
 
114623.4%
 

KBA13_CCM_2500
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.506715821
Minimum0
Maximum5
Zeros4158
Zeros (%)9.7%
Memory size334.8 KiB
2020-11-30T23:58:30.512263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.433446543
Coefficient of variation (CV)0.5718424606
Kurtosis-0.6836331488
Mean2.506715821
Median Absolute Deviation (MAD)1
Skewness-0.1399408078
Sum87715
Variance2.054768992
MonotocityNot monotonic
2020-11-30T23:58:30.596546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31231728.8%
 
2624514.6%
 
1474311.1%
 
041589.7%
 
441149.6%
 
534158.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
041589.7%
 
1474311.1%
 
2624514.6%
 
31231728.8%
 
441149.6%
 
534158.0%
 
ValueCountFrequency (%) 
534158.0%
 
441149.6%
 
31231728.8%
 
2624514.6%
 
1474311.1%
 
041589.7%
 

KBA13_CCM_2501
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.522319387
Minimum0
Maximum5
Zeros3962
Zeros (%)9.2%
Memory size334.8 KiB
2020-11-30T23:58:30.675415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.440686828
Coefficient of variation (CV)0.571175417
Kurtosis-0.7196319258
Mean2.522319387
Median Absolute Deviation (MAD)1
Skewness-0.1414759038
Sum88261
Variance2.075578536
MonotocityNot monotonic
2020-11-30T23:58:30.758692image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31292430.2%
 
1538212.6%
 
2517812.1%
 
439799.3%
 
039629.2%
 
535678.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
039629.2%
 
1538212.6%
 
2517812.1%
 
31292430.2%
 
439799.3%
 
535678.3%
 
ValueCountFrequency (%) 
535678.3%
 
439799.3%
 
31292430.2%
 
2517812.1%
 
1538212.6%
 
039629.2%
 

KBA13_CCM_3000
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.587591449
Minimum0
Maximum5
Zeros2530
Zeros (%)5.9%
Memory size334.8 KiB
2020-11-30T23:58:30.836964image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.366730654
Coefficient of variation (CV)0.5281864159
Kurtosis-0.6438252612
Mean2.587591449
Median Absolute Deviation (MAD)1
Skewness-0.1124593384
Sum90545
Variance1.867952679
MonotocityNot monotonic
2020-11-30T23:58:30.925199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31353531.6%
 
1645415.1%
 
2491211.5%
 
441439.7%
 
534188.0%
 
025305.9%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
025305.9%
 
1645415.1%
 
2491211.5%
 
31353531.6%
 
441439.7%
 
534188.0%
 
ValueCountFrequency (%) 
534188.0%
 
441439.7%
 
31353531.6%
 
2491211.5%
 
1645415.1%
 
025305.9%
 

KBA13_CCM_3001
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.609567901
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:31.009724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.511484397
Coefficient of variation (CV)0.5792086869
Kurtosis-1.582482765
Mean2.609567901
Median Absolute Deviation (MAD)2
Skewness0.1059577591
Sum91314
Variance2.284585084
MonotocityNot monotonic
2020-11-30T23:58:31.095765image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11525235.6%
 
4942422.0%
 
3660415.4%
 
537108.7%
 
22< 0.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
11525235.6%
 
22< 0.1%
 
3660415.4%
 
4942422.0%
 
537108.7%
 
ValueCountFrequency (%) 
537108.7%
 
4942422.0%
 
3660415.4%
 
22< 0.1%
 
11525235.6%
 

KBA13_FAB_ASIEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.951217421
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:31.190151image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.024181466
Coefficient of variation (CV)0.3470369411
Kurtosis-0.3069090302
Mean2.951217421
Median Absolute Deviation (MAD)1
Skewness0.05864913026
Sum103269
Variance1.048947676
MonotocityNot monotonic
2020-11-30T23:58:31.274939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31495134.9%
 
2783918.3%
 
4662015.5%
 
129136.8%
 
526696.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
129136.8%
 
2783918.3%
 
31495134.9%
 
4662015.5%
 
526696.2%
 
ValueCountFrequency (%) 
526696.2%
 
4662015.5%
 
31495134.9%
 
2783918.3%
 
129136.8%
 

KBA13_FAB_SONSTIGE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.977652035
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:31.366953image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.024722602
Coefficient of variation (CV)0.3441377939
Kurtosis-0.3152323078
Mean2.977652035
Median Absolute Deviation (MAD)1
Skewness0.02889213339
Sum104194
Variance1.050056411
MonotocityNot monotonic
2020-11-30T23:58:31.451327image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31493934.9%
 
2753417.6%
 
4695016.2%
 
128346.6%
 
527356.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
128346.6%
 
2753417.6%
 
31493934.9%
 
4695016.2%
 
527356.4%
 
ValueCountFrequency (%) 
527356.4%
 
4695016.2%
 
31493934.9%
 
2753417.6%
 
128346.6%
 

KBA13_FIAT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.089649063
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:31.542547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.018052746
Coefficient of variation (CV)0.3295043305
Kurtosis-0.3213688605
Mean3.089649063
Median Absolute Deviation (MAD)1
Skewness0.02552147606
Sum108113
Variance1.036431394
MonotocityNot monotonic
2020-11-30T23:58:31.626594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31499935.0%
 
4754217.6%
 
2693316.2%
 
533917.9%
 
121275.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
121275.0%
 
2693316.2%
 
31499935.0%
 
4754217.6%
 
533917.9%
 
ValueCountFrequency (%) 
533917.9%
 
4754217.6%
 
31499935.0%
 
2693316.2%
 
121275.0%
 

KBA13_FORD
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.939243256
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:31.717618image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.056529054
Coefficient of variation (CV)0.3594561463
Kurtosis-0.3835876062
Mean2.939243256
Median Absolute Deviation (MAD)1
Skewness0.08731757667
Sum102850
Variance1.116253641
MonotocityNot monotonic
2020-11-30T23:58:31.802092image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31452133.9%
 
2794618.6%
 
4628614.7%
 
132367.6%
 
530037.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
132367.6%
 
2794618.6%
 
31452133.9%
 
4628614.7%
 
530037.0%
 
ValueCountFrequency (%) 
530037.0%
 
4628614.7%
 
31452133.9%
 
2794618.6%
 
132367.6%
 

KBA13_GBZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.459905121
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:31.893433image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.095217427
Coefficient of variation (CV)0.3165455087
Kurtosis-0.543812113
Mean3.459905121
Median Absolute Deviation (MAD)1
Skewness-0.2405265577
Sum121069
Variance1.199501211
MonotocityNot monotonic
2020-11-30T23:58:31.980873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31281129.9%
 
4891120.8%
 
5737917.2%
 
242069.8%
 
116853.9%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
116853.9%
 
242069.8%
 
31281129.9%
 
4891120.8%
 
5737917.2%
 
ValueCountFrequency (%) 
5737917.2%
 
4891120.8%
 
31281129.9%
 
242069.8%
 
116853.9%
 

KBA13_HALTER_20
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.916123685
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:32.070804image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.008279619
Coefficient of variation (CV)0.3457602379
Kurtosis-0.2894615672
Mean2.916123685
Median Absolute Deviation (MAD)1
Skewness0.06827769837
Sum102041
Variance1.01662779
MonotocityNot monotonic
2020-11-30T23:58:32.154892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31489334.8%
 
2829919.4%
 
4656015.3%
 
129196.8%
 
523215.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
129196.8%
 
2829919.4%
 
31489334.8%
 
4656015.3%
 
523215.4%
 
ValueCountFrequency (%) 
523215.4%
 
4656015.3%
 
31489334.8%
 
2829919.4%
 
129196.8%
 

KBA13_HALTER_25
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.890517833
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:32.248317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.052528169
Coefficient of variation (CV)0.364131353
Kurtosis-0.387666274
Mean2.890517833
Median Absolute Deviation (MAD)1
Skewness0.03575421837
Sum101145
Variance1.107815547
MonotocityNot monotonic
2020-11-30T23:58:32.332940image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31459534.1%
 
2773518.1%
 
4640014.9%
 
137558.8%
 
525075.9%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
137558.8%
 
2773518.1%
 
31459534.1%
 
4640014.9%
 
525075.9%
 
ValueCountFrequency (%) 
525075.9%
 
4640014.9%
 
31459534.1%
 
2773518.1%
 
137558.8%
 

KBA13_HALTER_30
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.968078418
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:32.424963image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.065854024
Coefficient of variation (CV)0.3591057491
Kurtosis-0.4155336125
Mean2.968078418
Median Absolute Deviation (MAD)1
Skewness0.01338115631
Sum103859
Variance1.1360448
MonotocityNot monotonic
2020-11-30T23:58:32.508903image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31447733.8%
 
2725016.9%
 
4684116.0%
 
133897.9%
 
530357.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
133897.9%
 
2725016.9%
 
31447733.8%
 
4684116.0%
 
530357.1%
 
ValueCountFrequency (%) 
530357.1%
 
4684116.0%
 
31447733.8%
 
2725016.9%
 
133897.9%
 

KBA13_HALTER_35
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.026520348
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:32.601987image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.084514041
Coefficient of variation (CV)0.3583369402
Kurtosis-0.4866398696
Mean3.026520348
Median Absolute Deviation (MAD)1
Skewness-0.01655839185
Sum105904
Variance1.176170704
MonotocityNot monotonic
2020-11-30T23:58:32.686208image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31395432.6%
 
4735817.2%
 
2696616.3%
 
534918.2%
 
132237.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
132237.5%
 
2696616.3%
 
31395432.6%
 
4735817.2%
 
534918.2%
 
ValueCountFrequency (%) 
534918.2%
 
4735817.2%
 
31395432.6%
 
2696616.3%
 
132237.5%
 

KBA13_HALTER_40
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.025634431
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:32.777974image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.083151023
Coefficient of variation (CV)0.3579913727
Kurtosis-0.466207294
Mean3.025634431
Median Absolute Deviation (MAD)1
Skewness-0.009010278644
Sum105873
Variance1.173216139
MonotocityNot monotonic
2020-11-30T23:58:32.862799image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31418533.1%
 
4716416.7%
 
2688716.1%
 
535338.2%
 
132237.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
132237.5%
 
2688716.1%
 
31418533.1%
 
4716416.7%
 
535338.2%
 
ValueCountFrequency (%) 
535338.2%
 
4716416.7%
 
31418533.1%
 
2688716.1%
 
132237.5%
 

KBA13_HALTER_45
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.979595336
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:32.956915image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.080422363
Coefficient of variation (CV)0.3626070795
Kurtosis-0.476357731
Mean2.979595336
Median Absolute Deviation (MAD)1
Skewness0.03314485033
Sum104262
Variance1.167312482
MonotocityNot monotonic
2020-11-30T23:58:33.043050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31399232.7%
 
2749317.5%
 
4688716.1%
 
133377.8%
 
532837.7%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
133377.8%
 
2749317.5%
 
31399232.7%
 
4688716.1%
 
532837.7%
 
ValueCountFrequency (%) 
532837.7%
 
4688716.1%
 
31399232.7%
 
2749317.5%
 
133377.8%
 

KBA13_HALTER_50
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.912580018
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:33.134966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.065106196
Coefficient of variation (CV)0.3656916513
Kurtosis-0.4226919631
Mean2.912580018
Median Absolute Deviation (MAD)1
Skewness0.05749946121
Sum101917
Variance1.13445121
MonotocityNot monotonic
2020-11-30T23:58:33.219375image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31429533.4%
 
2784318.3%
 
4643215.0%
 
136238.5%
 
527996.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
136238.5%
 
2784318.3%
 
31429533.4%
 
4643215.0%
 
527996.5%
 
ValueCountFrequency (%) 
527996.5%
 
4643215.0%
 
31429533.4%
 
2784318.3%
 
136238.5%
 

KBA13_HALTER_55
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.917066758
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:33.311295image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.077931686
Coefficient of variation (CV)0.3695258885
Kurtosis-0.4628368657
Mean2.917066758
Median Absolute Deviation (MAD)1
Skewness0.07620353621
Sum102074
Variance1.161936719
MonotocityNot monotonic
2020-11-30T23:58:33.395640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31397532.6%
 
2799718.7%
 
4639314.9%
 
136388.5%
 
529897.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
136388.5%
 
2799718.7%
 
31397532.6%
 
4639314.9%
 
529897.0%
 
ValueCountFrequency (%) 
529897.0%
 
4639314.9%
 
31397532.6%
 
2799718.7%
 
136388.5%
 

KBA13_HALTER_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.980967078
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:33.491757image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.072402836
Coefficient of variation (CV)0.3597499764
Kurtosis-0.4449691209
Mean2.980967078
Median Absolute Deviation (MAD)1
Skewness0.0433804214
Sum104310
Variance1.150047843
MonotocityNot monotonic
2020-11-30T23:58:33.577100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31422033.2%
 
2751217.5%
 
4676615.8%
 
532677.6%
 
132277.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
132277.5%
 
2751217.5%
 
31422033.2%
 
4676615.8%
 
532677.6%
 
ValueCountFrequency (%) 
532677.6%
 
4676615.8%
 
31422033.2%
 
2751217.5%
 
132277.5%
 

KBA13_HALTER_65
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.144433013
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:33.668820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.058842034
Coefficient of variation (CV)0.33673544
Kurtosis-0.4407752625
Mean3.144433013
Median Absolute Deviation (MAD)1
Skewness-0.004953956063
Sum110030
Variance1.121146453
MonotocityNot monotonic
2020-11-30T23:58:33.752842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31438233.6%
 
4763317.8%
 
2652715.2%
 
542129.8%
 
122385.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122385.2%
 
2652715.2%
 
31438233.6%
 
4763317.8%
 
542129.8%
 
ValueCountFrequency (%) 
542129.8%
 
4763317.8%
 
31438233.6%
 
2652715.2%
 
122385.2%
 

KBA13_HALTER_66
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.129258116
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:33.845507image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.095173309
Coefficient of variation (CV)0.349978579
Kurtosis-0.5165664333
Mean3.129258116
Median Absolute Deviation (MAD)1
Skewness-0.04949573581
Sum109499
Variance1.199404577
MonotocityNot monotonic
2020-11-30T23:58:33.945032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31381132.2%
 
4769818.0%
 
2635914.8%
 
5435810.2%
 
127666.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
127666.5%
 
2635914.8%
 
31381132.2%
 
4769818.0%
 
5435810.2%
 
ValueCountFrequency (%) 
5435810.2%
 
4769818.0%
 
31381132.2%
 
2635914.8%
 
127666.5%
 

KBA13_HERST_ASIEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.969021491
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:34.072676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.054926336
Coefficient of variation (CV)0.355311115
Kurtosis-0.3977956134
Mean2.969021491
Median Absolute Deviation (MAD)1
Skewness0.05779372868
Sum103892
Variance1.112869575
MonotocityNot monotonic
2020-11-30T23:58:34.172101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31444733.7%
 
2771618.0%
 
4668615.6%
 
130857.2%
 
530587.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
130857.2%
 
2771618.0%
 
31444733.7%
 
4668615.6%
 
530587.1%
 
ValueCountFrequency (%) 
530587.1%
 
4668615.6%
 
31444733.7%
 
2771618.0%
 
130857.2%
 

KBA13_HERST_AUDI_VW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.985825332
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:34.278676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.028542526
Coefficient of variation (CV)0.3444751155
Kurtosis-0.2993771045
Mean2.985825332
Median Absolute Deviation (MAD)1
Skewness-0.006666181466
Sum104480
Variance1.057899727
MonotocityNot monotonic
2020-11-30T23:58:34.380138image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31516435.4%
 
2707416.5%
 
4702216.4%
 
129777.0%
 
527556.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
129777.0%
 
2707416.5%
 
31516435.4%
 
4702216.4%
 
527556.4%
 
ValueCountFrequency (%) 
527556.4%
 
4702216.4%
 
31516435.4%
 
2707416.5%
 
129777.0%
 

KBA13_HERST_BMW_BENZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.19338706
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:34.489067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.062887137
Coefficient of variation (CV)0.3328400589
Kurtosis-0.4321582652
Mean3.19338706
Median Absolute Deviation (MAD)1
Skewness-0.08406861717
Sum111743
Variance1.129729066
MonotocityNot monotonic
2020-11-30T23:58:34.589015image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31415733.1%
 
4831919.4%
 
2584813.7%
 
5440810.3%
 
122605.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122605.3%
 
2584813.7%
 
31415733.1%
 
4831919.4%
 
5440810.3%
 
ValueCountFrequency (%) 
5440810.3%
 
4831919.4%
 
31415733.1%
 
2584813.7%
 
122605.3%
 

KBA13_HERST_EUROPA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.073102423
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:34.696734image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.035052048
Coefficient of variation (CV)0.336810137
Kurtosis-0.3337666366
Mean3.073102423
Median Absolute Deviation (MAD)1
Skewness-0.006671404622
Sum107534
Variance1.071332743
MonotocityNot monotonic
2020-11-30T23:58:34.795834image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31494934.9%
 
4745917.4%
 
2670715.7%
 
533907.9%
 
124875.8%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
124875.8%
 
2670715.7%
 
31494934.9%
 
4745917.4%
 
533907.9%
 
ValueCountFrequency (%) 
533907.9%
 
4745917.4%
 
31494934.9%
 
2670715.7%
 
124875.8%
 

KBA13_HERST_FORD_OPEL
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.889517604
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:34.898011image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.058799382
Coefficient of variation (CV)0.3664277318
Kurtosis-0.4088396636
Mean2.889517604
Median Absolute Deviation (MAD)1
Skewness0.06753572166
Sum101110
Variance1.12105613
MonotocityNot monotonic
2020-11-30T23:58:34.990398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31431933.4%
 
2804318.8%
 
4630314.7%
 
136958.6%
 
526326.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
136958.6%
 
2804318.8%
 
31431933.4%
 
4630314.7%
 
526326.1%
 
ValueCountFrequency (%) 
526326.1%
 
4630314.7%
 
31431933.4%
 
2804318.8%
 
136958.6%
 

KBA13_HERST_SONST
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.977652035
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:35.083752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.024722602
Coefficient of variation (CV)0.3441377939
Kurtosis-0.3152323078
Mean2.977652035
Median Absolute Deviation (MAD)1
Skewness0.02889213339
Sum104194
Variance1.050056411
MonotocityNot monotonic
2020-11-30T23:58:35.169562image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31493934.9%
 
2753417.6%
 
4695016.2%
 
128346.6%
 
527356.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
128346.6%
 
2753417.6%
 
31493934.9%
 
4695016.2%
 
527356.4%
 
ValueCountFrequency (%) 
527356.4%
 
4695016.2%
 
31493934.9%
 
2753417.6%
 
128346.6%
 

KBA13_HHZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.491769547
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:35.262488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9579425649
Coefficient of variation (CV)0.2743430091
Kurtosis-0.4900038432
Mean3.491769547
Median Absolute Deviation (MAD)1
Skewness0.02499721362
Sum122184
Variance0.9176539576
MonotocityNot monotonic
2020-11-30T23:58:35.356490image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31530335.7%
 
4911921.3%
 
5640515.0%
 
236098.4%
 
15561.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
15561.3%
 
236098.4%
 
31530335.7%
 
4911921.3%
 
5640515.0%
 
ValueCountFrequency (%) 
5640515.0%
 
4911921.3%
 
31530335.7%
 
236098.4%
 
15561.3%
 

KBA13_KMH_0_140
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.267975537
Minimum0
Maximum5
Zeros4639
Zeros (%)10.8%
Memory size334.8 KiB
2020-11-30T23:58:35.477887image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.535181743
Coefficient of variation (CV)0.6768951947
Kurtosis-1.151833611
Mean2.267975537
Median Absolute Deviation (MAD)2
Skewness0.09110163436
Sum79361
Variance2.356782984
MonotocityNot monotonic
2020-11-30T23:58:35.576654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31223328.6%
 
11075325.1%
 
0463910.8%
 
440449.4%
 
530297.1%
 
22940.7%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0463910.8%
 
11075325.1%
 
22940.7%
 
31223328.6%
 
440449.4%
 
530297.1%
 
ValueCountFrequency (%) 
530297.1%
 
440449.4%
 
31223328.6%
 
22940.7%
 
11075325.1%
 
0463910.8%
 

KBA13_KMH_110
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
1
27923 
3
3995 
2
3074 
ValueCountFrequency (%) 
12792365.2%
 
339959.3%
 
230747.2%
 
(Missing)784118.3%
 
2020-11-30T23:58:35.687032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3499227.2%
 
03499227.2%
 
12792321.7%
 
n1568212.2%
 
a78416.1%
 
339953.1%
 
230742.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03499250.0%
 
12792339.9%
 
339955.7%
 
230744.4%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3499233.3%
 
03499233.3%
 
12792326.6%
 
339953.8%
 
230742.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3499227.2%
 
03499227.2%
 
12792321.7%
 
n1568212.2%
 
a78416.1%
 
339953.1%
 
230742.4%
 

KBA13_KMH_140
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.64826246
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:35.787130image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.38343299
Coefficient of variation (CV)0.5223927051
Kurtosis-1.359600704
Mean2.64826246
Median Absolute Deviation (MAD)1
Skewness0.1108905534
Sum92668
Variance1.913886838
MonotocityNot monotonic
2020-11-30T23:58:35.890323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11141526.7%
 
4863920.2%
 
3738017.2%
 
2441110.3%
 
531477.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
11141526.7%
 
2441110.3%
 
3738017.2%
 
4863920.2%
 
531477.3%
 
ValueCountFrequency (%) 
531477.3%
 
4863920.2%
 
3738017.2%
 
2441110.3%
 
11141526.7%
 

KBA13_KMH_140_210
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.8402492
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:36.000241image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9822085264
Coefficient of variation (CV)0.3458177284
Kurtosis-0.1789019925
Mean2.8402492
Median Absolute Deviation (MAD)1
Skewness0.01112302693
Sum99386
Variance0.9647335894
MonotocityNot monotonic
2020-11-30T23:58:36.092274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31588537.1%
 
2803118.7%
 
4589513.8%
 
134548.1%
 
517274.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
134548.1%
 
2803118.7%
 
31588537.1%
 
4589513.8%
 
517274.0%
 
ValueCountFrequency (%) 
517274.0%
 
4589513.8%
 
31588537.1%
 
2803118.7%
 
134548.1%
 

KBA13_KMH_180
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.865797897
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:36.194176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9805601957
Coefficient of variation (CV)0.3421595769
Kurtosis-0.2102885491
Mean2.865797897
Median Absolute Deviation (MAD)1
Skewness0.006359210553
Sum100280
Variance0.9614982974
MonotocityNot monotonic
2020-11-30T23:58:36.303484image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31559236.4%
 
2811518.9%
 
4632714.8%
 
132067.5%
 
517524.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
132067.5%
 
2811518.9%
 
31559236.4%
 
4632714.8%
 
517524.1%
 
ValueCountFrequency (%) 
517524.1%
 
4632714.8%
 
31559236.4%
 
2811518.9%
 
132067.5%
 

KBA13_KMH_210
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.109367856
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:36.415771image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9661240645
Coefficient of variation (CV)0.3107139809
Kurtosis-0.1522735456
Mean3.109367856
Median Absolute Deviation (MAD)1
Skewness0.009546520392
Sum108803
Variance0.933395708
MonotocityNot monotonic
2020-11-30T23:58:36.517547image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31596537.3%
 
4787918.4%
 
2646415.1%
 
529456.9%
 
117394.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
117394.1%
 
2646415.1%
 
31596537.3%
 
4787918.4%
 
529456.9%
 
ValueCountFrequency (%) 
529456.9%
 
4787918.4%
 
31596537.3%
 
2646415.1%
 
117394.1%
 

KBA13_KMH_211
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.497170782
Minimum0
Maximum5
Zeros5878
Zeros (%)13.7%
Memory size334.8 KiB
2020-11-30T23:58:36.623332image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.493756546
Coefficient of variation (CV)0.5981795707
Kurtosis-0.6857590169
Mean2.497170782
Median Absolute Deviation (MAD)1
Skewness-0.237370945
Sum87381
Variance2.23130862
MonotocityNot monotonic
2020-11-30T23:58:36.726659image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31243329.0%
 
2689116.1%
 
0587813.7%
 
440109.4%
 
536208.5%
 
121605.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0587813.7%
 
121605.0%
 
2689116.1%
 
31243329.0%
 
440109.4%
 
536208.5%
 
ValueCountFrequency (%) 
536208.5%
 
440109.4%
 
31243329.0%
 
2689116.1%
 
121605.0%
 
0587813.7%
 

KBA13_KMH_250
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.491855281
Minimum0
Maximum5
Zeros5951
Zeros (%)13.9%
Memory size334.8 KiB
2020-11-30T23:58:36.822037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.497959314
Coefficient of variation (CV)0.6011421791
Kurtosis-0.69998406
Mean2.491855281
Median Absolute Deviation (MAD)1
Skewness-0.2349678826
Sum87195
Variance2.243882106
MonotocityNot monotonic
2020-11-30T23:58:36.922752image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31237728.9%
 
2685616.0%
 
0595113.9%
 
440329.4%
 
536128.4%
 
121645.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0595113.9%
 
121645.1%
 
2685616.0%
 
31237728.9%
 
440329.4%
 
536128.4%
 
ValueCountFrequency (%) 
536128.4%
 
440329.4%
 
31237728.9%
 
2685616.0%
 
121645.1%
 
0595113.9%
 

KBA13_KMH_251
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
1
29889 
3
4642 
2
 
461
ValueCountFrequency (%) 
12988969.8%
 
3464210.8%
 
24611.1%
 
(Missing)784118.3%
 
2020-11-30T23:58:37.052588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3499227.2%
 
03499227.2%
 
12988923.3%
 
n1568212.2%
 
a78416.1%
 
346423.6%
 
24610.4%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03499250.0%
 
12988942.7%
 
346426.6%
 
24610.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3499233.3%
 
03499233.3%
 
12988928.5%
 
346424.4%
 
24610.4%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3499227.2%
 
03499227.2%
 
12988923.3%
 
n1568212.2%
 
a78416.1%
 
346423.6%
 
24610.4%
 

KBA13_KRSAQUOT
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.004029492
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Memory size334.8 KiB
2020-11-30T23:58:37.158533image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.050038844
Coefficient of variation (CV)0.3495434537
Kurtosis-0.3848951801
Mean3.004029492
Median Absolute Deviation (MAD)1
Skewness-0.01247588191
Sum105117
Variance1.102581574
MonotocityNot monotonic
2020-11-30T23:58:37.260384image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31456334.0%
 
4728817.0%
 
2709216.6%
 
130377.1%
 
530117.0%
 
01< 0.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
01< 0.1%
 
130377.1%
 
2709216.6%
 
31456334.0%
 
4728817.0%
 
530117.0%
 
ValueCountFrequency (%) 
530117.0%
 
4728817.0%
 
31456334.0%
 
2709216.6%
 
130377.1%
 
01< 0.1%
 

KBA13_KRSHERST_AUDI_VW
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.006144262
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Memory size334.8 KiB
2020-11-30T23:58:37.409971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.016365738
Coefficient of variation (CV)0.338096129
Kurtosis-0.3002311474
Mean3.006144262
Median Absolute Deviation (MAD)1
Skewness-0.0295976531
Sum105191
Variance1.032999314
MonotocityNot monotonic
2020-11-30T23:58:37.544269image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31499335.0%
 
4752017.6%
 
2709816.6%
 
127416.4%
 
526396.2%
 
01< 0.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
01< 0.1%
 
127416.4%
 
2709816.6%
 
31499335.0%
 
4752017.6%
 
526396.2%
 
ValueCountFrequency (%) 
526396.2%
 
4752017.6%
 
31499335.0%
 
2709816.6%
 
127416.4%
 
01< 0.1%
 

KBA13_KRSHERST_BMW_BENZ
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.117884088
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Memory size334.8 KiB
2020-11-30T23:58:37.642205image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.033528516
Coefficient of variation (CV)0.3314839445
Kurtosis-0.3505090775
Mean3.117884088
Median Absolute Deviation (MAD)1
Skewness0.01023389215
Sum109101
Variance1.068181193
MonotocityNot monotonic
2020-11-30T23:58:37.748159image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31492434.8%
 
4753817.6%
 
2660015.4%
 
537628.8%
 
121675.1%
 
01< 0.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
01< 0.1%
 
121675.1%
 
2660015.4%
 
31492434.8%
 
4753817.6%
 
537628.8%
 
ValueCountFrequency (%) 
537628.8%
 
4753817.6%
 
31492434.8%
 
2660015.4%
 
121675.1%
 
01< 0.1%
 

KBA13_KRSHERST_FORD_OPEL
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.983996342
Minimum0
Maximum5
Zeros1
Zeros (%)< 0.1%
Memory size334.8 KiB
2020-11-30T23:58:37.845537image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.051080816
Coefficient of variation (CV)0.3522393113
Kurtosis-0.3890971612
Mean2.983996342
Median Absolute Deviation (MAD)1
Skewness0.0005933018352
Sum104416
Variance1.104770883
MonotocityNot monotonic
2020-11-30T23:58:37.956461image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31453833.9%
 
2726317.0%
 
4712216.6%
 
131387.3%
 
529306.8%
 
01< 0.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
01< 0.1%
 
131387.3%
 
2726317.0%
 
31453833.9%
 
4712216.6%
 
529306.8%
 
ValueCountFrequency (%) 
529306.8%
 
4712216.6%
 
31453833.9%
 
2726317.0%
 
131387.3%
 
01< 0.1%
 

KBA13_KRSSEG_KLEIN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
2
32104 
1
 
1604
3
 
1283
0
 
1
ValueCountFrequency (%) 
23210475.0%
 
116043.7%
 
312833.0%
 
01< 0.1%
 
(Missing)784118.3%
 
2020-11-30T23:58:38.074469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
03499327.2%
 
.3499227.2%
 
23210425.0%
 
n1568212.2%
 
a78416.1%
 
116041.2%
 
312831.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03499350.0%
 
23210445.9%
 
116042.3%
 
312831.8%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
03499333.3%
 
.3499233.3%
 
23210430.6%
 
116041.5%
 
312831.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
03499327.2%
 
.3499227.2%
 
23210425.0%
 
n1568212.2%
 
a78416.1%
 
116041.2%
 
312831.0%
 

KBA13_KRSSEG_OBER
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
2
23003 
1
6469 
3
5511 
0
 
9
ValueCountFrequency (%) 
22300353.7%
 
1646915.1%
 
3551112.9%
 
09< 0.1%
 
(Missing)784118.3%
 
2020-11-30T23:58:38.193764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
03500127.2%
 
.3499227.2%
 
22300317.9%
 
n1568212.2%
 
a78416.1%
 
164695.0%
 
355114.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03500150.0%
 
22300332.9%
 
164699.2%
 
355117.9%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
03500133.3%
 
.3499233.3%
 
22300321.9%
 
164696.2%
 
355115.2%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
03500127.2%
 
.3499227.2%
 
22300317.9%
 
n1568212.2%
 
a78416.1%
 
164695.0%
 
355114.3%
 

KBA13_KRSSEG_VAN
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
2
21945 
1
6994 
3
6031 
0
 
22
ValueCountFrequency (%) 
22194551.2%
 
1699416.3%
 
3603114.1%
 
0220.1%
 
(Missing)784118.3%
 
2020-11-30T23:58:38.310422image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
03501427.2%
 
.3499227.2%
 
22194517.1%
 
n1568212.2%
 
a78416.1%
 
169945.4%
 
360314.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03501450.0%
 
22194531.4%
 
1699410.0%
 
360318.6%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
03501433.4%
 
.3499233.3%
 
22194520.9%
 
169946.7%
 
360315.7%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
03501427.2%
 
.3499227.2%
 
22194517.1%
 
n1568212.2%
 
a78416.1%
 
169945.4%
 
360314.7%
 

KBA13_KRSZUL_NEU
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
2
17187 
1
9065 
3
7672 
0
 
1068
ValueCountFrequency (%) 
21718740.1%
 
1906521.2%
 
3767217.9%
 
010682.5%
 
(Missing)784118.3%
 
2020-11-30T23:58:38.435981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
03606028.1%
 
.3499227.2%
 
21718713.4%
 
n1568212.2%
 
190657.1%
 
a78416.1%
 
376726.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03606051.5%
 
21718724.6%
 
1906513.0%
 
3767211.0%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
03606034.4%
 
.3499233.3%
 
21718716.4%
 
190658.6%
 
376727.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
03606028.1%
 
.3499227.2%
 
21718713.4%
 
n1568212.2%
 
190657.1%
 
a78416.1%
 
376726.0%
 

KBA13_KW_0_60
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.900205761
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:38.543207image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9719497444
Coefficient of variation (CV)0.335131306
Kurtosis-0.1501893384
Mean2.900205761
Median Absolute Deviation (MAD)1
Skewness0.03327559725
Sum101484
Variance0.9446863056
MonotocityNot monotonic
2020-11-30T23:58:38.650840image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31587137.1%
 
2803118.7%
 
4632914.8%
 
128286.6%
 
519334.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
128286.6%
 
2803118.7%
 
31587137.1%
 
4632914.8%
 
519334.5%
 
ValueCountFrequency (%) 
519334.5%
 
4632914.8%
 
31587137.1%
 
2803118.7%
 
128286.6%
 

KBA13_KW_110
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.477937814
Minimum0
Maximum5
Zeros5392
Zeros (%)12.6%
Memory size334.8 KiB
2020-11-30T23:58:38.755629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.45096929
Coefficient of variation (CV)0.5855551666
Kurtosis-0.6197638166
Mean2.477937814
Median Absolute Deviation (MAD)1
Skewness-0.2209237583
Sum86708
Variance2.10531188
MonotocityNot monotonic
2020-11-30T23:58:38.856277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31244429.1%
 
2732217.1%
 
0539212.6%
 
439949.3%
 
532297.5%
 
126116.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0539212.6%
 
126116.1%
 
2732217.1%
 
31244429.1%
 
439949.3%
 
532297.5%
 
ValueCountFrequency (%) 
532297.5%
 
439949.3%
 
31244429.1%
 
2732217.1%
 
126116.1%
 
0539212.6%
 

KBA13_KW_120
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.401291724
Minimum0
Maximum5
Zeros4056
Zeros (%)9.5%
Memory size334.8 KiB
2020-11-30T23:58:38.956464image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.529837762
Coefficient of variation (CV)0.6370895077
Kurtosis-1.107340162
Mean2.401291724
Median Absolute Deviation (MAD)1
Skewness-0.002013776439
Sum84026
Variance2.340403578
MonotocityNot monotonic
2020-11-30T23:58:39.057564image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31237928.9%
 
1960922.4%
 
4441810.3%
 
040569.5%
 
535168.2%
 
210142.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
040569.5%
 
1960922.4%
 
210142.4%
 
31237928.9%
 
4441810.3%
 
535168.2%
 
ValueCountFrequency (%) 
535168.2%
 
4441810.3%
 
31237928.9%
 
210142.4%
 
1960922.4%
 
040569.5%
 

KBA13_KW_121
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.524605624
Minimum0
Maximum5
Zeros4109
Zeros (%)9.6%
Memory size334.8 KiB
2020-11-30T23:58:39.154466image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.442077181
Coefficient of variation (CV)0.5712088918
Kurtosis-0.7043457054
Mean2.524605624
Median Absolute Deviation (MAD)1
Skewness-0.1481824457
Sum88341
Variance2.079586595
MonotocityNot monotonic
2020-11-30T23:58:39.254275image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31240729.0%
 
2588313.7%
 
1485611.3%
 
441879.8%
 
041099.6%
 
535508.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
041099.6%
 
1485611.3%
 
2588313.7%
 
31240729.0%
 
441879.8%
 
535508.3%
 
ValueCountFrequency (%) 
535508.3%
 
441879.8%
 
31240729.0%
 
2588313.7%
 
1485611.3%
 
041099.6%
 

KBA13_KW_30
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
1
24986 
2
6324 
3
3682 
ValueCountFrequency (%) 
12498658.3%
 
2632414.8%
 
336828.6%
 
(Missing)784118.3%
 
2020-11-30T23:58:39.366576image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3499227.2%
 
03499227.2%
 
12498619.4%
 
n1568212.2%
 
a78416.1%
 
263244.9%
 
336822.9%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03499250.0%
 
12498635.7%
 
263249.0%
 
336825.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3499233.3%
 
03499233.3%
 
12498623.8%
 
263246.0%
 
336823.5%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3499227.2%
 
03499227.2%
 
12498619.4%
 
n1568212.2%
 
a78416.1%
 
263244.9%
 
336822.9%
 

KBA13_KW_40
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.325017147
Minimum0
Maximum5
Zeros4472
Zeros (%)10.4%
Memory size334.8 KiB
2020-11-30T23:58:39.463907image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.393229032
Coefficient of variation (CV)0.5992338741
Kurtosis-0.704686508
Mean2.325017147
Median Absolute Deviation (MAD)1
Skewness-0.04606105805
Sum81357
Variance1.941087136
MonotocityNot monotonic
2020-11-30T23:58:39.565337image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31226728.6%
 
2638314.9%
 
1603614.1%
 
0447210.4%
 
434168.0%
 
524185.6%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0447210.4%
 
1603614.1%
 
2638314.9%
 
31226728.6%
 
434168.0%
 
524185.6%
 
ValueCountFrequency (%) 
524185.6%
 
434168.0%
 
31226728.6%
 
2638314.9%
 
1603614.1%
 
0447210.4%
 

KBA13_KW_50
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.288294467
Minimum0
Maximum5
Zeros6557
Zeros (%)15.3%
Memory size334.8 KiB
2020-11-30T23:58:39.661845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.435212517
Coefficient of variation (CV)0.6271974773
Kurtosis-0.6831539466
Mean2.288294467
Median Absolute Deviation (MAD)1
Skewness-0.1579449803
Sum80072
Variance2.059834969
MonotocityNot monotonic
2020-11-30T23:58:39.764635image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31179327.5%
 
2848519.8%
 
0655715.3%
 
434428.0%
 
124055.6%
 
523105.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0655715.3%
 
124055.6%
 
2848519.8%
 
31179327.5%
 
434428.0%
 
523105.4%
 
ValueCountFrequency (%) 
523105.4%
 
434428.0%
 
31179327.5%
 
2848519.8%
 
124055.6%
 
0655715.3%
 

KBA13_KW_60
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.25405807
Minimum0
Maximum5
Zeros6058
Zeros (%)14.1%
Memory size334.8 KiB
2020-11-30T23:58:39.857740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.414470424
Coefficient of variation (CV)0.6275217317
Kurtosis-0.693075675
Mean2.25405807
Median Absolute Deviation (MAD)1
Skewness-0.09688829034
Sum78874
Variance2.00072658
MonotocityNot monotonic
2020-11-30T23:58:39.967863image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31163627.2%
 
2812219.0%
 
0605814.1%
 
137178.7%
 
432907.7%
 
521695.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0605814.1%
 
137178.7%
 
2812219.0%
 
31163627.2%
 
432907.7%
 
521695.1%
 
ValueCountFrequency (%) 
521695.1%
 
432907.7%
 
31163627.2%
 
2812219.0%
 
137178.7%
 
0605814.1%
 

KBA13_KW_61_120
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.070387517
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:40.073880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9572562368
Coefficient of variation (CV)0.3117704952
Kurtosis-0.09054054441
Mean3.070387517
Median Absolute Deviation (MAD)1
Skewness-0.01680739368
Sum107439
Variance0.9163395029
MonotocityNot monotonic
2020-11-30T23:58:40.173989image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31626738.0%
 
4770818.0%
 
2651315.2%
 
525696.0%
 
119354.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
119354.5%
 
2651315.2%
 
31626738.0%
 
4770818.0%
 
525696.0%
 
ValueCountFrequency (%) 
525696.0%
 
4770818.0%
 
31626738.0%
 
2651315.2%
 
119354.5%
 

KBA13_KW_70
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.318987197
Minimum0
Maximum5
Zeros6512
Zeros (%)15.2%
Memory size334.8 KiB
2020-11-30T23:58:40.286317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.445389392
Coefficient of variation (CV)0.6232847656
Kurtosis-0.6829252876
Mean2.318987197
Median Absolute Deviation (MAD)1
Skewness-0.1770217097
Sum81146
Variance2.089150493
MonotocityNot monotonic
2020-11-30T23:58:40.390895image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31214328.3%
 
2808718.9%
 
0651215.2%
 
434558.1%
 
524825.8%
 
123135.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0651215.2%
 
123135.4%
 
2808718.9%
 
31214328.3%
 
434558.1%
 
524825.8%
 
ValueCountFrequency (%) 
524825.8%
 
434558.1%
 
31214328.3%
 
2808718.9%
 
123135.4%
 
0651215.2%
 

KBA13_KW_80
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.347450846
Minimum0
Maximum5
Zeros5694
Zeros (%)13.3%
Memory size334.8 KiB
2020-11-30T23:58:40.486254image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.423837254
Coefficient of variation (CV)0.606546142
Kurtosis-0.6505763796
Mean2.347450846
Median Absolute Deviation (MAD)1
Skewness-0.1527340119
Sum82142
Variance2.027312527
MonotocityNot monotonic
2020-11-30T23:58:40.587212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31218128.4%
 
2776718.1%
 
0569413.3%
 
435258.2%
 
132907.7%
 
525355.9%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0569413.3%
 
132907.7%
 
2776718.1%
 
31218128.4%
 
435258.2%
 
525355.9%
 
ValueCountFrequency (%) 
525355.9%
 
435258.2%
 
31218128.4%
 
2776718.1%
 
132907.7%
 
0569413.3%
 

KBA13_KW_90
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.40666438
Minimum0
Maximum5
Zeros6039
Zeros (%)14.1%
Memory size334.8 KiB
2020-11-30T23:58:40.686419image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.450577259
Coefficient of variation (CV)0.6027335056
Kurtosis-0.6415044715
Mean2.40666438
Median Absolute Deviation (MAD)1
Skewness-0.220363903
Sum84214
Variance2.104174384
MonotocityNot monotonic
2020-11-30T23:58:40.788615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31243929.0%
 
2769918.0%
 
0603914.1%
 
437888.8%
 
528306.6%
 
121975.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0603914.1%
 
121975.1%
 
2769918.0%
 
31243929.0%
 
437888.8%
 
528306.6%
 
ValueCountFrequency (%) 
528306.6%
 
437888.8%
 
31243929.0%
 
2769918.0%
 
121975.1%
 
0603914.1%
 

KBA13_MAZDA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.042838363
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:40.893774image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.005127964
Coefficient of variation (CV)0.3303257827
Kurtosis-0.2640366507
Mean3.042838363
Median Absolute Deviation (MAD)1
Skewness0.05457748601
Sum106475
Variance1.010282224
MonotocityNot monotonic
2020-11-30T23:58:41.008225image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31533035.8%
 
2728717.0%
 
4712416.6%
 
530417.1%
 
122105.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122105.2%
 
2728717.0%
 
31533035.8%
 
4712416.6%
 
530417.1%
 
ValueCountFrequency (%) 
530417.1%
 
4712416.6%
 
31533035.8%
 
2728717.0%
 
122105.2%
 

KBA13_MERCEDES
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.155092593
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:41.119505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.068023255
Coefficient of variation (CV)0.3385077375
Kurtosis-0.4399629851
Mean3.155092593
Median Absolute Deviation (MAD)1
Skewness-0.05607661795
Sum110403
Variance1.140673673
MonotocityNot monotonic
2020-11-30T23:58:41.222205image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31425933.3%
 
4792918.5%
 
2613014.3%
 
542449.9%
 
124305.7%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
124305.7%
 
2613014.3%
 
31425933.3%
 
4792918.5%
 
542449.9%
 
ValueCountFrequency (%) 
542449.9%
 
4792918.5%
 
31425933.3%
 
2613014.3%
 
124305.7%
 

KBA13_MOTOR
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Memory size334.8 KiB
3
21063 
2
6542 
4
4441 
1
2946 
ValueCountFrequency (%) 
32106349.2%
 
2654215.3%
 
4444110.4%
 
129466.9%
 
(Missing)784118.3%
 
2020-11-30T23:58:41.355438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters8
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3499227.2%
 
03499227.2%
 
32106316.4%
 
n1568212.2%
 
a78416.1%
 
265425.1%
 
444413.5%
 
129462.3%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6998454.5%
 
Other Punctuation3499227.2%
 
Lowercase Letter2352318.3%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03499250.0%
 
32106330.1%
 
265429.3%
 
444416.3%
 
129464.2%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34992100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10497681.7%
 
Latin2352318.3%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3499233.3%
 
03499233.3%
 
32106320.1%
 
265426.2%
 
444414.2%
 
129462.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1568266.7%
 
a784133.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3499227.2%
 
03499227.2%
 
32106316.4%
 
n1568212.2%
 
a78416.1%
 
265425.1%
 
444413.5%
 
129462.3%
 

KBA13_NISSAN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.987139918
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:41.461217image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.029698367
Coefficient of variation (CV)0.3447104574
Kurtosis-0.3472843047
Mean2.987139918
Median Absolute Deviation (MAD)1
Skewness0.08537756573
Sum104526
Variance1.060278728
MonotocityNot monotonic
2020-11-30T23:58:41.563951image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31466234.2%
 
2797418.6%
 
4676415.8%
 
529867.0%
 
126066.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
126066.1%
 
2797418.6%
 
31466234.2%
 
4676415.8%
 
529867.0%
 
ValueCountFrequency (%) 
529867.0%
 
4676415.8%
 
31466234.2%
 
2797418.6%
 
126066.1%
 

KBA13_OPEL
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.915437814
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:41.672383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.056852915
Coefficient of variation (CV)0.3625023006
Kurtosis-0.3915081285
Mean2.915437814
Median Absolute Deviation (MAD)1
Skewness0.06055182633
Sum102017
Variance1.116938084
MonotocityNot monotonic
2020-11-30T23:58:41.773381image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31449933.9%
 
2784018.3%
 
4637314.9%
 
135138.2%
 
527676.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
135138.2%
 
2784018.3%
 
31449933.9%
 
4637314.9%
 
527676.5%
 
ValueCountFrequency (%) 
527676.5%
 
4637314.9%
 
31449933.9%
 
2784018.3%
 
135138.2%
 

KBA13_PEUGEOT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.077560585
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:41.884853image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.021300125
Coefficient of variation (CV)0.3318537836
Kurtosis-0.3183910607
Mean3.077560585
Median Absolute Deviation (MAD)1
Skewness-0.01493393044
Sum107690
Variance1.043053944
MonotocityNot monotonic
2020-11-30T23:58:41.992924image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31491334.8%
 
4775218.1%
 
2678415.8%
 
532087.5%
 
123355.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
123355.5%
 
2678415.8%
 
31491334.8%
 
4775218.1%
 
532087.5%
 
ValueCountFrequency (%) 
532087.5%
 
4775218.1%
 
31491334.8%
 
2678415.8%
 
123355.5%
 

KBA13_RENAULT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.029492455
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:42.104916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.054833472
Coefficient of variation (CV)0.3481881824
Kurtosis-0.4062394234
Mean3.029492455
Median Absolute Deviation (MAD)1
Skewness0.02772027931
Sum106008
Variance1.112673653
MonotocityNot monotonic
2020-11-30T23:58:42.209081image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31446033.8%
 
2727017.0%
 
4711816.6%
 
533687.9%
 
127766.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
127766.5%
 
2727017.0%
 
31446033.8%
 
4711816.6%
 
533687.9%
 
ValueCountFrequency (%) 
533687.9%
 
4711816.6%
 
31446033.8%
 
2727017.0%
 
127766.5%
 

KBA13_SEG_GELAENDEWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.992055327
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:42.318118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.007385936
Coefficient of variation (CV)0.3366869344
Kurtosis-0.2497516774
Mean2.992055327
Median Absolute Deviation (MAD)1
Skewness0.002134709369
Sum104698
Variance1.014826423
MonotocityNot monotonic
2020-11-30T23:58:42.420946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31538035.9%
 
2721316.8%
 
4709916.6%
 
126916.3%
 
526096.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
126916.3%
 
2721316.8%
 
31538035.9%
 
4709916.6%
 
526096.1%
 
ValueCountFrequency (%) 
526096.1%
 
4709916.6%
 
31538035.9%
 
2721316.8%
 
126916.3%
 

KBA13_SEG_GROSSRAUMVANS
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.120227481
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:42.539575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.038748065
Coefficient of variation (CV)0.3329077996
Kurtosis-0.3781822911
Mean3.120227481
Median Absolute Deviation (MAD)1
Skewness-0.01844786057
Sum109183
Variance1.078997542
MonotocityNot monotonic
2020-11-30T23:58:42.640153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31459934.1%
 
4786418.4%
 
2657315.3%
 
537078.7%
 
122495.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122495.3%
 
2657315.3%
 
31459934.1%
 
4786418.4%
 
537078.7%
 
ValueCountFrequency (%) 
537078.7%
 
4786418.4%
 
31459934.1%
 
2657315.3%
 
122495.3%
 

KBA13_SEG_KLEINST
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.934785094
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:42.750658image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.028795487
Coefficient of variation (CV)0.3505522394
Kurtosis-0.3181684574
Mean2.934785094
Median Absolute Deviation (MAD)1
Skewness0.03604888473
Sum102694
Variance1.058420153
MonotocityNot monotonic
2020-11-30T23:58:42.859900image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31493834.9%
 
2771318.0%
 
4663115.5%
 
131557.4%
 
525556.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
131557.4%
 
2771318.0%
 
31493834.9%
 
4663115.5%
 
525556.0%
 
ValueCountFrequency (%) 
525556.0%
 
4663115.5%
 
31493834.9%
 
2771318.0%
 
131557.4%
 

KBA13_SEG_KLEINWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.917295382
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:42.974980image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.030619958
Coefficient of variation (CV)0.3532792615
Kurtosis-0.3124966748
Mean2.917295382
Median Absolute Deviation (MAD)1
Skewness0.0490139384
Sum102082
Variance1.062177498
MonotocityNot monotonic
2020-11-30T23:58:43.071026image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31498335.0%
 
2780718.2%
 
4640314.9%
 
132727.6%
 
525275.9%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
132727.6%
 
2780718.2%
 
31498335.0%
 
4640314.9%
 
525275.9%
 
ValueCountFrequency (%) 
525275.9%
 
4640314.9%
 
31498335.0%
 
2780718.2%
 
132727.6%
 

KBA13_SEG_KOMPAKTKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.969793096
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:43.169258image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.031097054
Coefficient of variation (CV)0.3471949127
Kurtosis-0.310451045
Mean2.969793096
Median Absolute Deviation (MAD)1
Skewness0.04925346084
Sum103919
Variance1.063161136
MonotocityNot monotonic
2020-11-30T23:58:43.259205image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31503635.1%
 
2755617.6%
 
4664115.5%
 
129156.8%
 
528446.6%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
129156.8%
 
2755617.6%
 
31503635.1%
 
4664115.5%
 
528446.6%
 
ValueCountFrequency (%) 
528446.6%
 
4664115.5%
 
31503635.1%
 
2755617.6%
 
129156.8%
 

KBA13_SEG_MINIVANS
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.048639689
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:43.367373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.008426888
Coefficient of variation (CV)0.3307792952
Kurtosis-0.2747016867
Mean3.048639689
Median Absolute Deviation (MAD)1
Skewness0.02351393009
Sum106678
Variance1.016924788
MonotocityNot monotonic
2020-11-30T23:58:43.457491image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31522935.6%
 
4735917.2%
 
2710316.6%
 
530127.0%
 
122895.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122895.3%
 
2710316.6%
 
31522935.6%
 
4735917.2%
 
530127.0%
 
ValueCountFrequency (%) 
530127.0%
 
4735917.2%
 
31522935.6%
 
2710316.6%
 
122895.3%
 

KBA13_SEG_MINIWAGEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.048668267
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:43.555608image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.014373537
Coefficient of variation (CV)0.3327267672
Kurtosis-0.2990576551
Mean3.048668267
Median Absolute Deviation (MAD)1
Skewness0.02842840517
Sum106679
Variance1.028953672
MonotocityNot monotonic
2020-11-30T23:58:43.648142image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31507535.2%
 
4734917.2%
 
2717816.8%
 
530787.2%
 
123125.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
123125.4%
 
2717816.8%
 
31507535.2%
 
4734917.2%
 
530787.2%
 
ValueCountFrequency (%) 
530787.2%
 
4734917.2%
 
31507535.2%
 
2717816.8%
 
123125.4%
 

KBA13_SEG_MITTELKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.06698674
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:43.747331image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.0176486
Coefficient of variation (CV)0.3318073035
Kurtosis-0.2913688177
Mean3.06698674
Median Absolute Deviation (MAD)1
Skewness0.01272670962
Sum107320
Variance1.035608673
MonotocityNot monotonic
2020-11-30T23:58:43.839616image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31518535.5%
 
4740817.3%
 
2687016.0%
 
532167.5%
 
123135.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
123135.4%
 
2687016.0%
 
31518535.5%
 
4740817.3%
 
532167.5%
 
ValueCountFrequency (%) 
532167.5%
 
4740817.3%
 
31518535.5%
 
2687016.0%
 
123135.4%
 

KBA13_SEG_OBEREMITTELKLASSE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.103109282
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:43.941800image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.030250101
Coefficient of variation (CV)0.3320057423
Kurtosis-0.3355953816
Mean3.103109282
Median Absolute Deviation (MAD)1
Skewness-0.01815906426
Sum108584
Variance1.06141527
MonotocityNot monotonic
2020-11-30T23:58:44.034451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31488034.7%
 
4775618.1%
 
2655615.3%
 
535028.2%
 
122985.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122985.4%
 
2655615.3%
 
31488034.7%
 
4775618.1%
 
535028.2%
 
ValueCountFrequency (%) 
535028.2%
 
4775618.1%
 
31488034.7%
 
2655615.3%
 
122985.4%
 

KBA13_SEG_OBERKLASSE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.472936671
Minimum0
Maximum5
Zeros3921
Zeros (%)9.2%
Memory size334.8 KiB
2020-11-30T23:58:44.126297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.487935258
Coefficient of variation (CV)0.6016875705
Kurtosis-0.9011867115
Mean2.472936671
Median Absolute Deviation (MAD)1
Skewness-0.04417266666
Sum86533
Variance2.213951331
MonotocityNot monotonic
2020-11-30T23:58:44.214755image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31242329.0%
 
1722216.9%
 
039219.2%
 
538629.0%
 
438028.9%
 
237628.8%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
039219.2%
 
1722216.9%
 
237628.8%
 
31242329.0%
 
438028.9%
 
538629.0%
 
ValueCountFrequency (%) 
538629.0%
 
438028.9%
 
31242329.0%
 
237628.8%
 
1722216.9%
 
039219.2%
 

KBA13_SEG_SONSTIGE
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.049525606
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:44.301979image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.945443462
Coefficient of variation (CV)0.3100296847
Kurtosis-0.1727362466
Mean3.049525606
Median Absolute Deviation (MAD)1
Skewness0.1204529625
Sum106709
Variance0.8938633399
MonotocityNot monotonic
2020-11-30T23:58:44.391914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31583937.0%
 
2775518.1%
 
4732817.1%
 
525756.0%
 
114953.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
114953.5%
 
2775518.1%
 
31583937.0%
 
4732817.1%
 
525756.0%
 
ValueCountFrequency (%) 
525756.0%
 
4732817.1%
 
31583937.0%
 
2775518.1%
 
114953.5%
 

KBA13_SEG_SPORTWAGEN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.562842936
Minimum0
Maximum5
Zeros3574
Zeros (%)8.3%
Memory size334.8 KiB
2020-11-30T23:58:44.486764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.443770546
Coefficient of variation (CV)0.5633472602
Kurtosis-0.7149111934
Mean2.562842936
Median Absolute Deviation (MAD)1
Skewness-0.08157509941
Sum89679
Variance2.08447339
MonotocityNot monotonic
2020-11-30T23:58:44.584701image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31155327.0%
 
2660515.4%
 
1510711.9%
 
540919.6%
 
440629.5%
 
035748.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
035748.3%
 
1510711.9%
 
2660515.4%
 
31155327.0%
 
440629.5%
 
540919.6%
 
ValueCountFrequency (%) 
540919.6%
 
440629.5%
 
31155327.0%
 
2660515.4%
 
1510711.9%
 
035748.3%
 

KBA13_SEG_UTILITIES
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.018890032
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:44.685513image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.99670105
Coefficient of variation (CV)0.330154805
Kurtosis-0.2299697165
Mean3.018890032
Median Absolute Deviation (MAD)1
Skewness0.02317531817
Sum105637
Variance0.993412983
MonotocityNot monotonic
2020-11-30T23:58:44.781262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31547136.1%
 
2724016.9%
 
4719716.8%
 
527186.3%
 
123665.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
123665.5%
 
2724016.9%
 
31547136.1%
 
4719716.8%
 
527186.3%
 
ValueCountFrequency (%) 
527186.3%
 
4719716.8%
 
31547136.1%
 
2724016.9%
 
123665.5%
 

KBA13_SEG_VAN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.089391861
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:44.897360image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.01825781
Coefficient of variation (CV)0.3295981398
Kurtosis-0.3126485866
Mean3.089391861
Median Absolute Deviation (MAD)1
Skewness-6.789843138e-05
Sum108104
Variance1.036848969
MonotocityNot monotonic
2020-11-30T23:58:45.005250image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31499835.0%
 
4769618.0%
 
2677615.8%
 
533137.7%
 
122095.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122095.2%
 
2677615.8%
 
31499835.0%
 
4769618.0%
 
533137.7%
 
ValueCountFrequency (%) 
533137.7%
 
4769618.0%
 
31499835.0%
 
2677615.8%
 
122095.2%
 

KBA13_SEG_WOHNMOBILE
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.498513946
Minimum0
Maximum5
Zeros3876
Zeros (%)9.0%
Memory size334.8 KiB
2020-11-30T23:58:45.109236image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.410226136
Coefficient of variation (CV)0.5644259612
Kurtosis-0.6148863598
Mean2.498513946
Median Absolute Deviation (MAD)1
Skewness-0.08593542387
Sum87428
Variance1.988737753
MonotocityNot monotonic
2020-11-30T23:58:45.208297image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31179527.5%
 
2742917.3%
 
1461110.8%
 
038769.0%
 
438318.9%
 
534508.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
038769.0%
 
1461110.8%
 
2742917.3%
 
31179527.5%
 
438318.9%
 
534508.1%
 
ValueCountFrequency (%) 
534508.1%
 
438318.9%
 
31179527.5%
 
2742917.3%
 
1461110.8%
 
038769.0%
 

KBA13_SITZE_4
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.128143576
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:45.296264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.08232484
Coefficient of variation (CV)0.3459958961
Kurtosis-0.4934549253
Mean3.128143576
Median Absolute Deviation (MAD)1
Skewness-0.03140613007
Sum109460
Variance1.171427059
MonotocityNot monotonic
2020-11-30T23:58:45.392442image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31395732.6%
 
4767917.9%
 
2651315.2%
 
542519.9%
 
125926.1%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
125926.1%
 
2651315.2%
 
31395732.6%
 
4767917.9%
 
542519.9%
 
ValueCountFrequency (%) 
542519.9%
 
4767917.9%
 
31395732.6%
 
2651315.2%
 
125926.1%
 

KBA13_SITZE_5
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.848994056
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:45.498365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.100817758
Coefficient of variation (CV)0.3863882257
Kurtosis-0.5513565952
Mean2.848994056
Median Absolute Deviation (MAD)1
Skewness0.07326066899
Sum99692
Variance1.211799737
MonotocityNot monotonic
2020-11-30T23:58:45.595672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31338331.2%
 
2807718.9%
 
4633514.8%
 
1448410.5%
 
527136.3%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
1448410.5%
 
2807718.9%
 
31338331.2%
 
4633514.8%
 
527136.3%
 
ValueCountFrequency (%) 
527136.3%
 
4633514.8%
 
31338331.2%
 
2807718.9%
 
1448410.5%
 

KBA13_SITZE_6
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.116512346
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:45.696570image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.080773424
Coefficient of variation (CV)0.3467893929
Kurtosis-0.4750621618
Mean3.116512346
Median Absolute Deviation (MAD)1
Skewness-0.05946495996
Sum109053
Variance1.168071194
MonotocityNot monotonic
2020-11-30T23:58:45.792627image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31397032.6%
 
4788918.4%
 
2635814.8%
 
540249.4%
 
127516.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
127516.4%
 
2635814.8%
 
31397032.6%
 
4788918.4%
 
540249.4%
 
ValueCountFrequency (%) 
540249.4%
 
4788918.4%
 
31397032.6%
 
2635814.8%
 
127516.4%
 

KBA13_TOYOTA
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.090963649
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:45.896332image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.02874386
Coefficient of variation (CV)0.3328230212
Kurtosis-0.3395771523
Mean3.090963649
Median Absolute Deviation (MAD)1
Skewness0.02565020996
Sum108159
Variance1.058313929
MonotocityNot monotonic
2020-11-30T23:58:45.994459image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31495434.9%
 
4740917.3%
 
2686816.0%
 
535418.3%
 
122205.2%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122205.2%
 
2686816.0%
 
31495434.9%
 
4740917.3%
 
535418.3%
 
ValueCountFrequency (%) 
535418.3%
 
4740917.3%
 
31495434.9%
 
2686816.0%
 
122205.2%
 

KBA13_VORB_0
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.226966164
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:46.098641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9750603119
Coefficient of variation (CV)0.3021600669
Kurtosis-0.2599456314
Mean3.226966164
Median Absolute Deviation (MAD)1
Skewness0.01076376957
Sum112918
Variance0.9507426118
MonotocityNot monotonic
2020-11-30T23:58:46.201379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31549236.2%
 
4854820.0%
 
2576213.5%
 
538849.1%
 
113063.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
113063.0%
 
2576213.5%
 
31549236.2%
 
4854820.0%
 
538849.1%
 
ValueCountFrequency (%) 
538849.1%
 
4854820.0%
 
31549236.2%
 
2576213.5%
 
113063.0%
 

KBA13_VORB_1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean3.044067215
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:46.326373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation0.9594691029
Coefficient of variation (CV)0.3151931397
Kurtosis-0.109918363
Mean3.044067215
Median Absolute Deviation (MAD)1
Skewness0.003252571558
Sum106518
Variance0.9205809595
MonotocityNot monotonic
2020-11-30T23:58:46.432639image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31616437.7%
 
4747317.4%
 
2687116.0%
 
524775.8%
 
120074.7%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
120074.7%
 
2687116.0%
 
31616437.7%
 
4747317.4%
 
524775.8%
 
ValueCountFrequency (%) 
524775.8%
 
4747317.4%
 
31616437.7%
 
2687116.0%
 
120074.7%
 

KBA13_VORB_1_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.919495885
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:46.545306image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9722246491
Coefficient of variation (CV)0.3330111387
Kurtosis-0.1589498644
Mean2.919495885
Median Absolute Deviation (MAD)1
Skewness-0.01607623048
Sum102159
Variance0.9452207684
MonotocityNot monotonic
2020-11-30T23:58:46.649441image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31593237.2%
 
2761417.8%
 
4669915.6%
 
128496.7%
 
518984.4%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
128496.7%
 
2761417.8%
 
31593237.2%
 
4669915.6%
 
518984.4%
 
ValueCountFrequency (%) 
518984.4%
 
4669915.6%
 
31593237.2%
 
2761417.8%
 
128496.7%
 

KBA13_VORB_2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.93638546
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:46.768194image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q33
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9476357974
Coefficient of variation (CV)0.3227218669
Kurtosis-0.08184159941
Mean2.93638546
Median Absolute Deviation (MAD)1
Skewness0.06447534477
Sum102750
Variance0.8980136044
MonotocityNot monotonic
2020-11-30T23:58:46.866476image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31619037.8%
 
2807718.9%
 
4647115.1%
 
122825.3%
 
519724.6%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
122825.3%
 
2807718.9%
 
31619037.8%
 
4647115.1%
 
519724.6%
 
ValueCountFrequency (%) 
519724.6%
 
4647115.1%
 
31619037.8%
 
2807718.9%
 
122825.3%
 

KBA13_VORB_3
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.153949474
Minimum0
Maximum5
Zeros7322
Zeros (%)17.1%
Memory size334.8 KiB
2020-11-30T23:58:46.967720image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.430405424
Coefficient of variation (CV)0.6640849479
Kurtosis-0.7536674813
Mean2.153949474
Median Absolute Deviation (MAD)1
Skewness-0.07771420394
Sum75371
Variance2.046059678
MonotocityNot monotonic
2020-11-30T23:58:47.063536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31131526.4%
 
2867720.3%
 
0732217.1%
 
428826.7%
 
128596.7%
 
519374.5%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
0732217.1%
 
128596.7%
 
2867720.3%
 
31131526.4%
 
428826.7%
 
519374.5%
 
ValueCountFrequency (%) 
519374.5%
 
428826.7%
 
31131526.4%
 
2867720.3%
 
128596.7%
 
0732217.1%
 

KBA13_VW
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7841
Missing (%)18.3%
Infinite0
Infinite (%)0.0%
Mean2.971965021
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:47.161867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.017065913
Coefficient of variation (CV)0.3422200147
Kurtosis-0.26345719
Mean2.971965021
Median Absolute Deviation (MAD)1
Skewness-0.001956172708
Sum103995
Variance1.034423071
MonotocityNot monotonic
2020-11-30T23:58:47.265671image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31537135.9%
 
2717816.8%
 
4690916.1%
 
129456.9%
 
525896.0%
 
(Missing)784118.3%
 
ValueCountFrequency (%) 
129456.9%
 
2717816.8%
 
31537135.9%
 
4690916.1%
 
525896.0%
 
ValueCountFrequency (%) 
525896.0%
 
4690916.1%
 
31537135.9%
 
2717816.8%
 
129456.9%
 

KK_KUNDENTYP
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing25035
Missing (%)58.4%
Infinite0
Infinite (%)0.0%
Mean3.43004832
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:47.367489image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.641739556
Coefficient of variation (CV)0.4786345271
Kurtosis-1.184722381
Mean3.43004832
Median Absolute Deviation (MAD)1
Skewness0.08552217891
Sum61048
Variance2.695308769
MonotocityNot monotonic
2020-11-30T23:58:47.466594image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
336998.6%
 
232517.6%
 
530427.1%
 
126656.2%
 
426366.2%
 
625055.8%
 
(Missing)2503558.4%
 
ValueCountFrequency (%) 
126656.2%
 
232517.6%
 
336998.6%
 
426366.2%
 
530427.1%
 
625055.8%
 
ValueCountFrequency (%) 
625055.8%
 
530427.1%
 
426366.2%
 
336998.6%
 
232517.6%
 
126656.2%
 

KKK
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8303
Missing (%)19.4%
Infinite0
Infinite (%)0.0%
Mean2.538980597
Minimum0
Maximum4
Zeros1539
Zeros (%)3.6%
Memory size334.8 KiB
2020-11-30T23:58:47.562068image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.107346637
Coefficient of variation (CV)0.4361382827
Kurtosis-0.5666071325
Mean2.538980597
Median Absolute Deviation (MAD)1
Skewness-0.4405677757
Sum87671
Variance1.226216575
MonotocityNot monotonic
2020-11-30T23:58:47.668290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31203428.1%
 
2869420.3%
 
4730617.1%
 
1495711.6%
 
015393.6%
 
(Missing)830319.4%
 
ValueCountFrequency (%) 
015393.6%
 
1495711.6%
 
2869420.3%
 
31203428.1%
 
4730617.1%
 
ValueCountFrequency (%) 
4730617.1%
 
31203428.1%
 
2869420.3%
 
1495711.6%
 
015393.6%
 

KOMBIALTER
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.566292345
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:47.772347image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q14
median4
Q34
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.035281428
Coefficient of variation (CV)0.4457185993
Kurtosis0.9302558464
Mean4.566292345
Median Absolute Deviation (MAD)0
Skewness1.463743409
Sum195588
Variance4.142370491
MonotocityNot monotonic
2020-11-30T23:58:47.867329image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
42788265.1%
 
9696816.3%
 
3597013.9%
 
214253.3%
 
15881.4%
 
ValueCountFrequency (%) 
15881.4%
 
214253.3%
 
3597013.9%
 
42788265.1%
 
9696816.3%
 
ValueCountFrequency (%) 
9696816.3%
 
42788265.1%
 
3597013.9%
 
214253.3%
 
15881.4%
 

KONSUMNAEHE
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing6926
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean3.157685131
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:47.986355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.510183656
Coefficient of variation (CV)0.4782565689
Kurtosis-1.054811317
Mean3.157685131
Median Absolute Deviation (MAD)1
Skewness0.07199608532
Sum113383
Variance2.280654676
MonotocityNot monotonic
2020-11-30T23:58:48.078105image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
3799618.7%
 
5736617.2%
 
1686416.0%
 
4633814.8%
 
2597013.9%
 
612022.8%
 
71710.4%
 
(Missing)692616.2%
 
ValueCountFrequency (%) 
1686416.0%
 
2597013.9%
 
3799618.7%
 
4633814.8%
 
5736617.2%
 
612022.8%
 
71710.4%
 
ValueCountFrequency (%) 
71710.4%
 
612022.8%
 
5736617.2%
 
4633814.8%
 
3799618.7%
 
2597013.9%
 
1686416.0%
 

KONSUMZELLE
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Memory size334.8 KiB
0
28509 
1
6697 
(Missing)
7627 
ValueCountFrequency (%) 
02850966.6%
 
1669715.6%
 
(Missing)762717.8%
 

LP_FAMILIE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct12
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean4.143911963
Minimum0
Maximum11
Zeros8073
Zeros (%)18.8%
Memory size334.8 KiB
2020-11-30T23:58:48.182726image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q310
95-th percentile11
Maximum11
Range11
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.399888205
Coefficient of variation (CV)1.061771641
Kurtosis-1.488851472
Mean4.143911963
Median Absolute Deviation (MAD)2
Skewness0.6166546802
Sum175101
Variance19.35901622
MonotocityNot monotonic
2020-11-30T23:58:48.278048image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
11220128.5%
 
10859720.1%
 
0807318.8%
 
2702616.4%
 
11433210.1%
 
96521.5%
 
86331.5%
 
73460.8%
 
51860.4%
 
41110.3%
 
6680.2%
 
3300.1%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
0807318.8%
 
11220128.5%
 
2702616.4%
 
3300.1%
 
41110.3%
 
51860.4%
 
6680.2%
 
73460.8%
 
86331.5%
 
96521.5%
 
ValueCountFrequency (%) 
11433210.1%
 
10859720.1%
 
96521.5%
 
86331.5%
 
73460.8%
 
6680.2%
 
51860.4%
 
41110.3%
 
3300.1%
 
2702616.4%
 

LP_FAMILIE_GROB
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean2.350656727
Minimum0
Maximum5
Zeros8073
Zeros (%)18.8%
Memory size334.8 KiB
2020-11-30T23:58:48.369505image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q35
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.982321876
Coefficient of variation (CV)0.8433055552
Kurtosis-1.522411662
Mean2.350656727
Median Absolute Deviation (MAD)2
Skewness0.3710142793
Sum99327
Variance3.929600021
MonotocityNot monotonic
2020-11-30T23:58:48.465402image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
51358131.7%
 
11220128.5%
 
0807318.8%
 
2702616.4%
 
410472.4%
 
33270.8%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
0807318.8%
 
11220128.5%
 
2702616.4%
 
33270.8%
 
410472.4%
 
51358131.7%
 
ValueCountFrequency (%) 
51358131.7%
 
410472.4%
 
33270.8%
 
2702616.4%
 
11220128.5%
 
0807318.8%
 

LP_LEBENSPHASE_FEIN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct41
Distinct (%)0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean17.77517454
Minimum0
Maximum40
Zeros8156
Zeros (%)19.0%
Memory size334.8 KiB
2020-11-30T23:58:48.582806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16
median15
Q332
95-th percentile40
Maximum40
Range40
Interquartile range (IQR)26

Descriptive statistics

Standard deviation14.09661615
Coefficient of variation (CV)0.7930507869
Kurtosis-1.375561596
Mean17.77517454
Median Absolute Deviation (MAD)15
Skewness0.2681290165
Sum751090
Variance198.714587
MonotocityNot monotonic
2020-11-30T23:58:48.718932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%) 
0815619.0%
 
631867.4%
 
4024335.7%
 
822885.3%
 
3820964.9%
 
1219924.7%
 
1319654.6%
 
2018484.3%
 
3117304.0%
 
3215993.7%
 
1915843.7%
 
1515463.6%
 
3614443.4%
 
3913373.1%
 
1612743.0%
 
3711632.7%
 
96711.6%
 
56651.6%
 
175831.4%
 
355721.3%
 
114621.1%
 
74161.0%
 
283620.8%
 
343600.8%
 
303500.8%
 
Other values (16)21735.1%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
0815619.0%
 
11240.3%
 
21150.3%
 
3730.2%
 
4640.1%
 
56651.6%
 
631867.4%
 
74161.0%
 
822885.3%
 
96711.6%
 
ValueCountFrequency (%) 
4024335.7%
 
3913373.1%
 
3820964.9%
 
3711632.7%
 
3614443.4%
 
355721.3%
 
343600.8%
 
332340.5%
 
3215993.7%
 
3117304.0%
 

LP_LEBENSPHASE_GROB
Real number (ℝ≥0)

MISSING
ZEROS

Distinct13
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean5.313193705
Minimum0
Maximum12
Zeros8135
Zeros (%)19.0%
Memory size334.8 KiB
2020-11-30T23:58:48.840491image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q310
95-th percentile12
Maximum12
Range12
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.475535267
Coefficient of variation (CV)0.8423437043
Kurtosis-1.379090455
Mean5.313193705
Median Absolute Deviation (MAD)4
Skewness0.4161018538
Sum224509
Variance20.03041593
MonotocityNot monotonic
2020-11-30T23:58:48.950372image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
12847319.8%
 
0813519.0%
 
2655515.3%
 
3524112.2%
 
540799.5%
 
1033297.8%
 
429446.9%
 
1111662.7%
 
87991.9%
 
95831.4%
 
13760.9%
 
63270.8%
 
72480.6%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
0813519.0%
 
13760.9%
 
2655515.3%
 
3524112.2%
 
429446.9%
 
540799.5%
 
63270.8%
 
72480.6%
 
87991.9%
 
95831.4%
 
ValueCountFrequency (%) 
12847319.8%
 
1111662.7%
 
1033297.8%
 
95831.4%
 
87991.9%
 
72480.6%
 
63270.8%
 
540799.5%
 
429446.9%
 
3524112.2%
 

LP_STATUS_FEIN
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean5.936528222
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:49.047823image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q39
95-th percentile10
Maximum10
Range9
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.412463023
Coefficient of variation (CV)0.5748246948
Kurtosis-1.497602482
Mean5.936528222
Median Absolute Deviation (MAD)4
Skewness-0.1710078775
Sum250848
Variance11.64490388
MonotocityNot monotonic
2020-11-30T23:58:49.136779image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
10912721.3%
 
9859920.1%
 
1820819.2%
 
5598114.0%
 
339999.3%
 
425175.9%
 
618074.2%
 
712913.0%
 
26131.4%
 
81130.3%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
1820819.2%
 
26131.4%
 
339999.3%
 
425175.9%
 
5598114.0%
 
618074.2%
 
712913.0%
 
81130.3%
 
9859920.1%
 
10912721.3%
 
ValueCountFrequency (%) 
10912721.3%
 
9859920.1%
 
81130.3%
 
712913.0%
 
618074.2%
 
5598114.0%
 
425175.9%
 
339999.3%
 
26131.4%
 
1820819.2%
 

LP_STATUS_GROB
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean2.924908295
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:49.225103image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.481674669
Coefficient of variation (CV)0.5065713245
Kurtosis-1.472269366
Mean2.924908295
Median Absolute Deviation (MAD)1
Skewness0.1424502095
Sum123592
Variance2.195359824
MonotocityNot monotonic
2020-11-30T23:58:49.309263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21249729.2%
 
5912721.3%
 
1882120.6%
 
4871220.3%
 
330987.2%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
1882120.6%
 
21249729.2%
 
330987.2%
 
4871220.3%
 
5912721.3%
 
ValueCountFrequency (%) 
5912721.3%
 
4871220.3%
 
330987.2%
 
21249729.2%
 
1882120.6%
 

MIN_GEBAEUDEJAHR
Real number (ℝ≥0)

MISSING

Distinct31
Distinct (%)0.1%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean1992.880475
Minimum1985
Maximum2015
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:49.411301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1985
5-th percentile1992
Q11992
median1992
Q31992
95-th percentile1997
Maximum2015
Range30
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.481306554
Coefficient of variation (CV)0.001245085486
Kurtosis21.88518508
Mean1992.880475
Median Absolute Deviation (MAD)0
Skewness4.10538424
Sum70161350
Variance6.156882217
MonotocityNot monotonic
2020-11-30T23:58:49.558301image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%) 
19922575360.1%
 
199438058.9%
 
199312192.8%
 
19959792.3%
 
19966981.6%
 
19975711.3%
 
19913010.7%
 
20002860.7%
 
19902510.6%
 
20011650.4%
 
19891370.3%
 
20021300.3%
 
20051220.3%
 
19991150.3%
 
19981140.3%
 
2003880.2%
 
2004720.2%
 
2006630.1%
 
1988560.1%
 
2008520.1%
 
2007350.1%
 
2009310.1%
 
2012300.1%
 
1987290.1%
 
2010260.1%
 
Other values (6)780.2%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
19856< 0.1%
 
19864< 0.1%
 
1987290.1%
 
1988560.1%
 
19891370.3%
 
19902510.6%
 
19913010.7%
 
19922575360.1%
 
199312192.8%
 
199438058.9%
 
ValueCountFrequency (%) 
201510< 0.1%
 
201416< 0.1%
 
201320< 0.1%
 
2012300.1%
 
2011220.1%
 
2010260.1%
 
2009310.1%
 
2008520.1%
 
2007350.1%
 
2006630.1%
 

MOBI_RASTER
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean2.689030279
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:49.701149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.593513192
Coefficient of variation (CV)0.5925977123
Kurtosis-1.113040927
Mean2.689030279
Median Absolute Deviation (MAD)2
Skewness0.4297424015
Sum94670
Variance2.539284292
MonotocityNot monotonic
2020-11-30T23:58:49.805541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11259429.4%
 
3617114.4%
 
4517512.1%
 
2496011.6%
 
5489311.4%
 
614133.3%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
11259429.4%
 
2496011.6%
 
3617114.4%
 
4517512.1%
 
5489311.4%
 
614133.3%
 
ValueCountFrequency (%) 
614133.3%
 
5489311.4%
 
4517512.1%
 
3617114.4%
 
2496011.6%
 
11259429.4%
 

MOBI_REGIO
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing8537
Missing (%)19.9%
Infinite0
Infinite (%)0.0%
Mean3.332487754
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:49.896454image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q35
95-th percentile5
Maximum6
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.414333578
Coefficient of variation (CV)0.4244077346
Kurtosis-1.183413878
Mean3.332487754
Median Absolute Deviation (MAD)1
Skewness-0.3428078294
Sum114291
Variance2.000339471
MonotocityNot monotonic
2020-11-30T23:58:49.989932image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
5941122.0%
 
4819519.1%
 
3631614.7%
 
1533212.4%
 
2501911.7%
 
6230.1%
 
(Missing)853719.9%
 
ValueCountFrequency (%) 
1533212.4%
 
2501911.7%
 
3631614.7%
 
4819519.1%
 
5941122.0%
 
6230.1%
 
ValueCountFrequency (%) 
6230.1%
 
5941122.0%
 
4819519.1%
 
3631614.7%
 
2501911.7%
 
1533212.4%
 

NATIONALITAET_KZ
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size334.8 KiB
1
34381 
0
7226 
2
 
725
3
 
501
ValueCountFrequency (%) 
13438180.3%
 
0722616.9%
 
27251.7%
 
35011.2%
 
2020-11-30T23:58:50.104160image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
13438180.3%
 
0722616.9%
 
27251.7%
 
35011.2%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number42833100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
13438180.3%
 
0722616.9%
 
27251.7%
 
35011.2%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42833100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
13438180.3%
 
0722616.9%
 
27251.7%
 
35011.2%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII42833100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
13438180.3%
 
0722616.9%
 
27251.7%
 
35011.2%
 

ONLINE_AFFINITAET
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean2.586628801
Minimum0
Maximum5
Zeros2105
Zeros (%)4.9%
Memory size334.8 KiB
2020-11-30T23:58:50.203183image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.363056204
Coefficient of variation (CV)0.526962432
Kurtosis-0.8529404168
Mean2.586628801
Median Absolute Deviation (MAD)1
Skewness0.1456840456
Sum109298
Variance1.857922215
MonotocityNot monotonic
2020-11-30T23:58:50.302377image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
21420433.2%
 
4864020.2%
 
1688916.1%
 
3632214.8%
 
540959.6%
 
021054.9%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
021054.9%
 
1688916.1%
 
21420433.2%
 
3632214.8%
 
4864020.2%
 
540959.6%
 
ValueCountFrequency (%) 
540959.6%
 
4864020.2%
 
3632214.8%
 
21420433.2%
 
1688916.1%
 
021054.9%
 

ORTSGR_KLS9
Real number (ℝ≥0)

MISSING

Distinct10
Distinct (%)< 0.1%
Missing7783
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean5.127931526
Minimum0
Maximum9
Zeros1
Zeros (%)< 0.1%
Memory size334.8 KiB
2020-11-30T23:58:50.390855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median5
Q37
95-th percentile9
Maximum9
Range9
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.386302146
Coefficient of variation (CV)0.4653537461
Kurtosis-1.025678258
Mean5.127931526
Median Absolute Deviation (MAD)2
Skewness0.1476881671
Sum179734
Variance5.694437931
MonotocityNot monotonic
2020-11-30T23:58:50.470880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%) 
5620814.5%
 
4526712.3%
 
9462610.8%
 
3446210.4%
 
736128.4%
 
235528.3%
 
627676.5%
 
827236.4%
 
118324.3%
 
01< 0.1%
 
(Missing)778318.2%
 
ValueCountFrequency (%) 
01< 0.1%
 
118324.3%
 
235528.3%
 
3446210.4%
 
4526712.3%
 
5620814.5%
 
627676.5%
 
736128.4%
 
827236.4%
 
9462610.8%
 
ValueCountFrequency (%) 
9462610.8%
 
827236.4%
 
736128.4%
 
627676.5%
 
5620814.5%
 
4526712.3%
 
3446210.4%
 
235528.3%
 
118324.3%
 
01< 0.1%
 

OST_WEST_KZ
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Memory size334.8 KiB
W
26773 
O
8433 
ValueCountFrequency (%) 
W2677362.5%
 
O843319.7%
 
(Missing)762717.8%
 
2020-11-30T23:58:50.567603image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters4
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
W2677346.1%
 
n1525426.3%
 
O843314.5%
 
a762713.1%
 

Most occurring categories

ValueCountFrequency (%) 
Uppercase Letter3520660.6%
 
Lowercase Letter2288139.4%
 

Most frequent Uppercase Letter characters

ValueCountFrequency (%) 
W2677376.0%
 
O843324.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1525466.7%
 
a762733.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Latin58087100.0%
 

Most frequent Latin characters

ValueCountFrequency (%) 
W2677346.1%
 
n1525426.3%
 
O843314.5%
 
a762713.1%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII58087100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
W2677346.1%
 
n1525426.3%
 
O843314.5%
 
a762713.1%
 

PLZ8_ANTG1
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8044
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean2.392049211
Minimum0
Maximum4
Zeros248
Zeros (%)0.6%
Memory size334.8 KiB
2020-11-30T23:58:50.656092image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9775248398
Coefficient of variation (CV)0.4086558233
Kurtosis-0.8455810211
Mean2.392049211
Median Absolute Deviation (MAD)1
Skewness0.01838367356
Sum83217
Variance0.9555548123
MonotocityNot monotonic
2020-11-30T23:58:50.751272image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21176427.5%
 
31104625.8%
 
1679115.9%
 
4494011.5%
 
02480.6%
 
(Missing)804418.8%
 
ValueCountFrequency (%) 
02480.6%
 
1679115.9%
 
21176427.5%
 
31104625.8%
 
4494011.5%
 
ValueCountFrequency (%) 
4494011.5%
 
31104625.8%
 
21176427.5%
 
1679115.9%
 
02480.6%
 

PLZ8_ANTG2
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8044
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean2.705970278
Minimum0
Maximum4
Zeros395
Zeros (%)0.9%
Memory size334.8 KiB
2020-11-30T23:58:50.856813image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9279767831
Coefficient of variation (CV)0.3429367982
Kurtosis-0.3268998623
Mean2.705970278
Median Absolute Deviation (MAD)1
Skewness-0.35576459
Sum94138
Variance0.8611409099
MonotocityNot monotonic
2020-11-30T23:58:50.953056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31372932.1%
 
21048224.5%
 
4726817.0%
 
129156.8%
 
03950.9%
 
(Missing)804418.8%
 
ValueCountFrequency (%) 
03950.9%
 
129156.8%
 
21048224.5%
 
31372932.1%
 
4726817.0%
 
ValueCountFrequency (%) 
4726817.0%
 
31372932.1%
 
21048224.5%
 
129156.8%
 
03950.9%
 

PLZ8_ANTG3
Categorical

MISSING

Distinct4
Distinct (%)< 0.1%
Missing8044
Missing (%)18.8%
Memory size334.8 KiB
1
11601 
2
10626 
0
6493 
3
6069 
ValueCountFrequency (%) 
11160127.1%
 
21062624.8%
 
0649315.2%
 
3606914.2%
 
(Missing)804418.8%
 
2020-11-30T23:58:51.073894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
04128232.1%
 
.3478927.1%
 
n1608812.5%
 
1116019.0%
 
2106268.3%
 
a80446.3%
 
360694.7%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6957854.1%
 
Other Punctuation3478927.1%
 
Lowercase Letter2413218.8%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
04128259.3%
 
11160116.7%
 
21062615.3%
 
360698.7%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34789100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1608866.7%
 
a804433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10436781.2%
 
Latin2413218.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
04128239.6%
 
.3478933.3%
 
11160111.1%
 
21062610.2%
 
360695.8%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1608866.7%
 
a804433.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
04128232.1%
 
.3478927.1%
 
n1608812.5%
 
1116019.0%
 
2106268.3%
 
a80446.3%
 
360694.7%
 

PLZ8_ANTG4
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing8044
Missing (%)18.8%
Memory size334.8 KiB
0
18122 
1
12136 
2
4531 
ValueCountFrequency (%) 
01812242.3%
 
11213628.3%
 
2453110.6%
 
(Missing)804418.8%
 
2020-11-30T23:58:51.194066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters6
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
05291141.2%
 
.3478927.1%
 
n1608812.5%
 
1121369.4%
 
a80446.3%
 
245313.5%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number6957854.1%
 
Other Punctuation3478927.1%
 
Lowercase Letter2413218.8%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
05291176.0%
 
11213617.4%
 
245316.5%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.34789100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1608866.7%
 
a804433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10436781.2%
 
Latin2413218.8%
 

Most frequent Common characters

ValueCountFrequency (%) 
05291150.7%
 
.3478933.3%
 
11213611.6%
 
245314.3%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1608866.7%
 
a804433.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
05291141.2%
 
.3478927.1%
 
n1608812.5%
 
1121369.4%
 
a80446.3%
 
245313.5%
 

PLZ8_BAUMAX
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8044
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean1.776222369
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:51.301395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.356137183
Coefficient of variation (CV)0.7634951605
Kurtosis0.6939711328
Mean1.776222369
Median Absolute Deviation (MAD)0
Skewness1.50278047
Sum61793
Variance1.839108059
MonotocityNot monotonic
2020-11-30T23:58:51.391896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
12435956.9%
 
534108.0%
 
228406.6%
 
421645.1%
 
320164.7%
 
(Missing)804418.8%
 
ValueCountFrequency (%) 
12435956.9%
 
228406.6%
 
320164.7%
 
421645.1%
 
534108.0%
 
ValueCountFrequency (%) 
534108.0%
 
421645.1%
 
320164.7%
 
228406.6%
 
12435956.9%
 

PLZ8_GBZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8044
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean3.424501998
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:51.488016image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.08586932
Coefficient of variation (CV)0.3170882424
Kurtosis-0.518171033
Mean3.424501998
Median Absolute Deviation (MAD)1
Skewness-0.2095506686
Sum119135
Variance1.179112179
MonotocityNot monotonic
2020-11-30T23:58:51.583943image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31309430.6%
 
4883320.6%
 
5683216.0%
 
2433110.1%
 
116994.0%
 
(Missing)804418.8%
 
ValueCountFrequency (%) 
116994.0%
 
2433110.1%
 
31309430.6%
 
4883320.6%
 
5683216.0%
 
ValueCountFrequency (%) 
5683216.0%
 
4883320.6%
 
31309430.6%
 
2433110.1%
 
116994.0%
 

PLZ8_HHZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing8044
Missing (%)18.8%
Infinite0
Infinite (%)0.0%
Mean3.532093478
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:51.685801image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.9548177559
Coefficient of variation (CV)0.2703262985
Kurtosis-0.5503825339
Mean3.532093478
Median Absolute Deviation (MAD)1
Skewness0.01781335321
Sum122878
Variance0.911676947
MonotocityNot monotonic
2020-11-30T23:58:51.783910image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31499235.0%
 
4921021.5%
 
5678615.8%
 
233317.8%
 
14701.1%
 
(Missing)804418.8%
 
ValueCountFrequency (%) 
14701.1%
 
233317.8%
 
31499235.0%
 
4921021.5%
 
5678615.8%
 
ValueCountFrequency (%) 
5678615.8%
 
4921021.5%
 
31499235.0%
 
233317.8%
 
14701.1%
 

PRAEGENDE_JUGENDJAHRE
Real number (ℝ≥0)

ZEROS

Distinct16
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.464454976
Minimum0
Maximum15
Zeros7365
Zeros (%)17.2%
Memory size334.8 KiB
2020-11-30T23:58:51.896080image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median4
Q36
95-th percentile12
Maximum15
Range15
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.76727788
Coefficient of variation (CV)0.8438382513
Kurtosis0.1653395666
Mean4.464454976
Median Absolute Deviation (MAD)3
Skewness0.8460481672
Sum191226
Variance14.19238263
MonotocityNot monotonic
2020-11-30T23:58:52.000026image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%) 
0736517.2%
 
3691816.2%
 
5581413.6%
 
1437410.2%
 
839349.2%
 
435368.3%
 
622535.3%
 
919254.5%
 
219104.5%
 
1111312.6%
 
1411082.6%
 
109842.3%
 
156541.5%
 
74331.0%
 
123070.7%
 
131870.4%
 
ValueCountFrequency (%) 
0736517.2%
 
1437410.2%
 
219104.5%
 
3691816.2%
 
435368.3%
 
5581413.6%
 
622535.3%
 
74331.0%
 
839349.2%
 
919254.5%
 
ValueCountFrequency (%) 
156541.5%
 
1411082.6%
 
131870.4%
 
123070.7%
 
1111312.6%
 
109842.3%
 
919254.5%
 
839349.2%
 
74331.0%
 
622535.3%
 

REGIOTYP
Real number (ℝ≥0)

MISSING
ZEROS

Distinct8
Distinct (%)< 0.1%
Missing8303
Missing (%)19.4%
Infinite0
Infinite (%)0.0%
Mean4.116333623
Minimum0
Maximum7
Zeros1539
Zeros (%)3.6%
Memory size334.8 KiB
2020-11-30T23:58:52.101793image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median5
Q36
95-th percentile7
Maximum7
Range7
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.007499103
Coefficient of variation (CV)0.4876910587
Kurtosis-0.9975851073
Mean4.116333623
Median Absolute Deviation (MAD)1
Skewness-0.3850581869
Sum142137
Variance4.030052647
MonotocityNot monotonic
2020-11-30T23:58:52.193649image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
6810218.9%
 
5667615.6%
 
2469311.0%
 
3443710.4%
 
432277.5%
 
731147.3%
 
127426.4%
 
015393.6%
 
(Missing)830319.4%
 
ValueCountFrequency (%) 
015393.6%
 
127426.4%
 
2469311.0%
 
3443710.4%
 
432277.5%
 
5667615.6%
 
6810218.9%
 
731147.3%
 
ValueCountFrequency (%) 
731147.3%
 
6810218.9%
 
5667615.6%
 
432277.5%
 
3443710.4%
 
2469311.0%
 
127426.4%
 
015393.6%
 

RELAT_AB
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing7783
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean2.964308131
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:52.301410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum9
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.354194449
Coefficient of variation (CV)0.4568332268
Kurtosis-1.01429886
Mean2.964308131
Median Absolute Deviation (MAD)1
Skewness0.04114216777
Sum103899
Variance1.833842605
MonotocityNot monotonic
2020-11-30T23:58:52.395488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
31203728.1%
 
1710216.6%
 
5662015.5%
 
2479911.2%
 
4448810.5%
 
94< 0.1%
 
(Missing)778318.2%
 
ValueCountFrequency (%) 
1710216.6%
 
2479911.2%
 
31203728.1%
 
4448810.5%
 
5662015.5%
 
94< 0.1%
 
ValueCountFrequency (%) 
94< 0.1%
 
5662015.5%
 
4448810.5%
 
31203728.1%
 
2479911.2%
 
1710216.6%
 

RETOURTYP_BK_S
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean3.717500887
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:52.499447image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median3
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.177935793
Coefficient of variation (CV)0.3168622763
Kurtosis-1.155276074
Mean3.717500887
Median Absolute Deviation (MAD)1
Skewness-0.2384469704
Sum157083
Variance1.387532733
MonotocityNot monotonic
2020-11-30T23:58:52.604919image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
51686539.4%
 
31555236.3%
 
2508311.9%
 
437278.7%
 
110282.4%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
110282.4%
 
2508311.9%
 
31555236.3%
 
437278.7%
 
51686539.4%
 
ValueCountFrequency (%) 
51686539.4%
 
437278.7%
 
31555236.3%
 
2508311.9%
 
110282.4%
 

RT_KEIN_ANREIZ
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean2.486143652
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:52.709763image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile4
Maximum5
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.231514876
Coefficient of variation (CV)0.4953514553
Kurtosis-1.257202805
Mean2.486143652
Median Absolute Deviation (MAD)1
Skewness0.2235742372
Sum105052
Variance1.51662889
MonotocityNot monotonic
2020-11-30T23:58:52.806545image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
11219528.5%
 
41056724.7%
 
21055824.6%
 
3760117.7%
 
513343.1%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
11219528.5%
 
21055824.6%
 
3760117.7%
 
41056724.7%
 
513343.1%
 
ValueCountFrequency (%) 
513343.1%
 
41056724.7%
 
3760117.7%
 
21055824.6%
 
11219528.5%
 

RT_SCHNAEPPCHEN
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing578
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean4.135013608
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:52.910787image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.204262119
Coefficient of variation (CV)0.2912353461
Kurtosis0.1900730322
Mean4.135013608
Median Absolute Deviation (MAD)0
Skewness-1.188843958
Sum174725
Variance1.450247252
MonotocityNot monotonic
2020-11-30T23:58:53.003262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
52428256.7%
 
4716816.7%
 
3485611.3%
 
241269.6%
 
118234.3%
 
(Missing)5781.3%
 
ValueCountFrequency (%) 
118234.3%
 
241269.6%
 
3485611.3%
 
4716816.7%
 
52428256.7%
 
ValueCountFrequency (%) 
52428256.7%
 
4716816.7%
 
3485611.3%
 
241269.6%
 
118234.3%
 

RT_UEBERGROESSE
Real number (ℝ≥0)

MISSING

Distinct6
Distinct (%)< 0.1%
Missing6217
Missing (%)14.5%
Infinite0
Infinite (%)0.0%
Mean2.201578545
Minimum0
Maximum5
Zeros277
Zeros (%)0.6%
Memory size334.8 KiB
2020-11-30T23:58:53.103498image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.300816966
Coefficient of variation (CV)0.5908564874
Kurtosis-0.4102020626
Mean2.201578545
Median Absolute Deviation (MAD)1
Skewness0.805670382
Sum80613
Variance1.692124778
MonotocityNot monotonic
2020-11-30T23:58:53.196128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
11430033.4%
 
2944322.0%
 
3621914.5%
 
532627.6%
 
431157.3%
 
02770.6%
 
(Missing)621714.5%
 
ValueCountFrequency (%) 
02770.6%
 
11430033.4%
 
2944322.0%
 
3621914.5%
 
431157.3%
 
532627.6%
 
ValueCountFrequency (%) 
532627.6%
 
431157.3%
 
3621914.5%
 
2944322.0%
 
11430033.4%
 
02770.6%
 

SEMIO_DOM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.734200266
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:53.283196image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.55819491
Coefficient of variation (CV)0.3291358249
Kurtosis-0.500908479
Mean4.734200266
Median Absolute Deviation (MAD)1
Skewness-0.5581897379
Sum202780
Variance2.427971377
MonotocityNot monotonic
2020-11-30T23:58:53.370290image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61211328.3%
 
51105625.8%
 
3816519.1%
 
742099.8%
 
439659.3%
 
216793.9%
 
116463.8%
 
ValueCountFrequency (%) 
116463.8%
 
216793.9%
 
3816519.1%
 
439659.3%
 
51105625.8%
 
61211328.3%
 
742099.8%
 
ValueCountFrequency (%) 
742099.8%
 
61211328.3%
 
51105625.8%
 
439659.3%
 
3816519.1%
 
216793.9%
 
116463.8%
 

SEMIO_ERL
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.121004833
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:53.457833image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q13
median6
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.821891891
Coefficient of variation (CV)0.3557684381
Kurtosis-1.62954724
Mean5.121004833
Median Absolute Deviation (MAD)1
Skewness-0.2234640092
Sum219348
Variance3.319290062
MonotocityNot monotonic
2020-11-30T23:58:53.542633image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
71712240.0%
 
31278429.8%
 
6559913.1%
 
4542812.7%
 
28362.0%
 
57751.8%
 
12890.7%
 
ValueCountFrequency (%) 
12890.7%
 
28362.0%
 
31278429.8%
 
4542812.7%
 
57751.8%
 
6559913.1%
 
71712240.0%
 
ValueCountFrequency (%) 
71712240.0%
 
6559913.1%
 
57751.8%
 
4542812.7%
 
31278429.8%
 
28362.0%
 
12890.7%
 

SEMIO_FAM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.754371629
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:53.640088image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.842996668
Coefficient of variation (CV)0.4908935103
Kurtosis-1.346249781
Mean3.754371629
Median Absolute Deviation (MAD)2
Skewness-0.00163620448
Sum160811
Variance3.396636718
MonotocityNot monotonic
2020-11-30T23:58:53.719492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61102425.7%
 
3756917.7%
 
2724116.9%
 
1600414.0%
 
4547112.8%
 
5453910.6%
 
79852.3%
 
ValueCountFrequency (%) 
1600414.0%
 
2724116.9%
 
3756917.7%
 
4547112.8%
 
5453910.6%
 
61102425.7%
 
79852.3%
 
ValueCountFrequency (%) 
79852.3%
 
61102425.7%
 
5453910.6%
 
4547112.8%
 
3756917.7%
 
2724116.9%
 
1600414.0%
 

SEMIO_KAEM
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6629001
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:53.807922image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.724022833
Coefficient of variation (CV)0.3697318827
Kurtosis-0.882555238
Mean4.6629001
Median Absolute Deviation (MAD)1
Skewness-0.5788193459
Sum199726
Variance2.972254729
MonotocityNot monotonic
2020-11-30T23:58:53.891884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61553036.3%
 
3860120.1%
 
5784818.3%
 
737948.9%
 
232357.6%
 
122755.3%
 
415503.6%
 
ValueCountFrequency (%) 
122755.3%
 
232357.6%
 
3860120.1%
 
415503.6%
 
5784818.3%
 
61553036.3%
 
737948.9%
 
ValueCountFrequency (%) 
737948.9%
 
61553036.3%
 
5784818.3%
 
415503.6%
 
3860120.1%
 
232357.6%
 
122755.3%
 

SEMIO_KRIT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.001377443
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:53.979430image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.867499434
Coefficient of variation (CV)0.3733970202
Kurtosis-0.9711424866
Mean5.001377443
Median Absolute Deviation (MAD)1
Skewness-0.4867083686
Sum214224
Variance3.487554135
MonotocityNot monotonic
2020-11-30T23:58:54.060118image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
71361331.8%
 
3951622.2%
 
6813719.0%
 
4504111.8%
 
536158.4%
 
124985.8%
 
24131.0%
 
ValueCountFrequency (%) 
124985.8%
 
24131.0%
 
3951622.2%
 
4504111.8%
 
536158.4%
 
6813719.0%
 
71361331.8%
 
ValueCountFrequency (%) 
71361331.8%
 
6813719.0%
 
536158.4%
 
4504111.8%
 
3951622.2%
 
24131.0%
 
124985.8%
 

SEMIO_KULT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.175145332
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:54.157455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.665687779
Coefficient of variation (CV)0.524602059
Kurtosis-0.7486463522
Mean3.175145332
Median Absolute Deviation (MAD)1
Skewness0.3631143376
Sum136001
Variance2.774515776
MonotocityNot monotonic
2020-11-30T23:58:54.246653image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31111425.9%
 
1935921.8%
 
4738117.2%
 
2576113.4%
 
6428210.0%
 
539959.3%
 
79412.2%
 
ValueCountFrequency (%) 
1935921.8%
 
2576113.4%
 
31111425.9%
 
4738117.2%
 
539959.3%
 
6428210.0%
 
79412.2%
 
ValueCountFrequency (%) 
79412.2%
 
6428210.0%
 
539959.3%
 
4738117.2%
 
31111425.9%
 
2576113.4%
 
1935921.8%
 

SEMIO_LUST
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.380244204
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:54.336536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q15
median5
Q37
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.533266119
Coefficient of variation (CV)0.2849807669
Kurtosis0.7101308139
Mean5.380244204
Median Absolute Deviation (MAD)1
Skewness-0.9207383944
Sum230452
Variance2.350904993
MonotocityNot monotonic
2020-11-30T23:58:54.415717image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
51488034.7%
 
71440433.6%
 
4533512.5%
 
6451510.5%
 
115553.6%
 
211932.8%
 
39512.2%
 
ValueCountFrequency (%) 
115553.6%
 
211932.8%
 
39512.2%
 
4533512.5%
 
51488034.7%
 
6451510.5%
 
71440433.6%
 
ValueCountFrequency (%) 
71440433.6%
 
6451510.5%
 
51488034.7%
 
4533512.5%
 
39512.2%
 
211932.8%
 
115553.6%
 

SEMIO_MAT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.407256088
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:54.509834image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.797015233
Coefficient of variation (CV)0.527408327
Kurtosis-1.266137162
Mean3.407256088
Median Absolute Deviation (MAD)2
Skewness0.08461637848
Sum145943
Variance3.229263747
MonotocityNot monotonic
2020-11-30T23:58:54.594672image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
5944322.0%
 
1904621.1%
 
2729517.0%
 
4586513.7%
 
3549612.8%
 
6467210.9%
 
710162.4%
 
ValueCountFrequency (%) 
1904621.1%
 
2729517.0%
 
3549612.8%
 
4586513.7%
 
5944322.0%
 
6467210.9%
 
710162.4%
 
ValueCountFrequency (%) 
710162.4%
 
6467210.9%
 
5944322.0%
 
4586513.7%
 
3549612.8%
 
2729517.0%
 
1904621.1%
 

SEMIO_PFLICHT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.340368408
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:54.677764image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.5705514
Coefficient of variation (CV)0.4701731092
Kurtosis-0.8052317006
Mean3.340368408
Median Absolute Deviation (MAD)1
Skewness0.1591918315
Sum143078
Variance2.4666317
MonotocityNot monotonic
2020-11-30T23:58:54.754425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
5960622.4%
 
2907721.2%
 
4880620.6%
 
3686916.0%
 
1621814.5%
 
713033.0%
 
69542.2%
 
ValueCountFrequency (%) 
1621814.5%
 
2907721.2%
 
3686916.0%
 
4880620.6%
 
5960622.4%
 
69542.2%
 
713033.0%
 
ValueCountFrequency (%) 
713033.0%
 
69542.2%
 
5960622.4%
 
4880620.6%
 
3686916.0%
 
2907721.2%
 
1621814.5%
 

SEMIO_RAT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.190250508
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:54.847435image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.27880199
Coefficient of variation (CV)0.4008468887
Kurtosis0.6222150951
Mean3.190250508
Median Absolute Deviation (MAD)1
Skewness0.4555809547
Sum136648
Variance1.635334531
MonotocityNot monotonic
2020-11-30T23:58:54.957274image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
41366331.9%
 
31247929.1%
 
2860820.1%
 
140129.4%
 
521515.0%
 
710562.5%
 
68642.0%
 
ValueCountFrequency (%) 
140129.4%
 
2860820.1%
 
31247929.1%
 
41366331.9%
 
521515.0%
 
68642.0%
 
710562.5%
 
ValueCountFrequency (%) 
710562.5%
 
68642.0%
 
521515.0%
 
41366331.9%
 
31247929.1%
 
2860820.1%
 
140129.4%
 

SEMIO_REL
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.463847968
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:55.162665image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.095989089
Coefficient of variation (CV)0.6051042391
Kurtosis-0.9540579729
Mean3.463847968
Median Absolute Deviation (MAD)1
Skewness0.5506181158
Sum148367
Variance4.39317026
MonotocityNot monotonic
2020-11-30T23:58:55.282475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
1929121.7%
 
3840419.6%
 
7816319.1%
 
2752417.6%
 
4609214.2%
 
528476.6%
 
65121.2%
 
ValueCountFrequency (%) 
1929121.7%
 
2752417.6%
 
3840419.6%
 
4609214.2%
 
528476.6%
 
65121.2%
 
7816319.1%
 
ValueCountFrequency (%) 
7816319.1%
 
65121.2%
 
528476.6%
 
4609214.2%
 
3840419.6%
 
2752417.6%
 
1929121.7%
 

SEMIO_SOZ
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.616580674
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:55.382834image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q35
95-th percentile6
Maximum7
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.681521507
Coefficient of variation (CV)0.4649478772
Kurtosis-1.211719382
Mean3.616580674
Median Absolute Deviation (MAD)1
Skewness0.2339116242
Sum154909
Variance2.827514578
MonotocityNot monotonic
2020-11-30T23:58:55.498913image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
21271829.7%
 
6758217.7%
 
4700016.3%
 
3599714.0%
 
5570213.3%
 
128936.8%
 
79412.2%
 
ValueCountFrequency (%) 
128936.8%
 
21271829.7%
 
3599714.0%
 
4700016.3%
 
5570213.3%
 
6758217.7%
 
79412.2%
 
ValueCountFrequency (%) 
79412.2%
 
6758217.7%
 
5570213.3%
 
4700016.3%
 
3599714.0%
 
21271829.7%
 
128936.8%
 

SEMIO_TRADV
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.796115145
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:55.618458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.331867757
Coefficient of variation (CV)0.4763279363
Kurtosis0.6031976483
Mean2.796115145
Median Absolute Deviation (MAD)1
Skewness0.5348095254
Sum119766
Variance1.773871721
MonotocityNot monotonic
2020-11-30T23:58:55.736400image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
31644838.4%
 
1979422.9%
 
4848819.8%
 
2544412.7%
 
69432.2%
 
59412.2%
 
77751.8%
 
ValueCountFrequency (%) 
1979422.9%
 
2544412.7%
 
31644838.4%
 
4848819.8%
 
59412.2%
 
69432.2%
 
77751.8%
 
ValueCountFrequency (%) 
77751.8%
 
69432.2%
 
59412.2%
 
4848819.8%
 
31644838.4%
 
2544412.7%
 
1979422.9%
 

SEMIO_VERT
Real number (ℝ≥0)

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.884785096
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:55.874682image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.094340695
Coefficient of variation (CV)0.5391136557
Kurtosis-1.331876835
Mean3.884785096
Median Absolute Deviation (MAD)2
Skewness0.007811952371
Sum166397
Variance4.386262945
MonotocityNot monotonic
2020-11-30T23:58:55.986395image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
1857020.0%
 
4665315.5%
 
7619714.5%
 
5611814.3%
 
2569113.3%
 
6568413.3%
 
339209.2%
 
ValueCountFrequency (%) 
1857020.0%
 
2569113.3%
 
339209.2%
 
4665315.5%
 
5611814.3%
 
6568413.3%
 
7619714.5%
 
ValueCountFrequency (%) 
7619714.5%
 
6568413.3%
 
5611814.3%
 
4665315.5%
 
339209.2%
 
2569113.3%
 
1857020.0%
 

SHOPPER_TYP
Real number (ℝ)

ZEROS

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.307356477
Minimum-1
Maximum3
Zeros6092
Zeros (%)14.2%
Memory size334.8 KiB
2020-11-30T23:58:56.101660image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q10
median1
Q33
95-th percentile3
Maximum3
Range4
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.470658836
Coefficient of variation (CV)1.124910352
Kurtosis-1.305865392
Mean1.307356477
Median Absolute Deviation (MAD)1
Skewness-0.2602733026
Sum55998
Variance2.162837411
MonotocityNot monotonic
2020-11-30T23:58:56.201746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
31367231.9%
 
1916021.4%
 
-1733217.1%
 
2657715.4%
 
0609214.2%
 
ValueCountFrequency (%) 
-1733217.1%
 
0609214.2%
 
1916021.4%
 
2657715.4%
 
31367231.9%
 
ValueCountFrequency (%) 
31367231.9%
 
2657715.4%
 
1916021.4%
 
0609214.2%
 
-1733217.1%
 

SOHO_KZ
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Memory size334.8 KiB
0
35614 
1
 
330
(Missing)
6889 
ValueCountFrequency (%) 
03561483.1%
 
13300.8%
 
(Missing)688916.1%
 

STRUKTURTYP
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing7784
Missing (%)18.2%
Memory size334.8 KiB
3
23144 
1
6763 
2
5142 
ValueCountFrequency (%) 
32314454.0%
 
1676315.8%
 
2514212.0%
 
(Missing)778418.2%
 
2020-11-30T23:58:56.346240image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters7
Unique unicode categories3 ?
Unique unicode scripts2 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
.3504927.3%
 
03504927.3%
 
32314418.0%
 
n1556812.1%
 
a77846.1%
 
167635.3%
 
251424.0%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number7009854.6%
 
Other Punctuation3504927.3%
 
Lowercase Letter2335218.2%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
03504950.0%
 
32314433.0%
 
167639.6%
 
251427.3%
 

Most frequent Other Punctuation characters

ValueCountFrequency (%) 
.35049100.0%
 

Most frequent Lowercase Letter characters

ValueCountFrequency (%) 
n1556866.7%
 
a778433.3%
 

Most occurring scripts

ValueCountFrequency (%) 
Common10514781.8%
 
Latin2335218.2%
 

Most frequent Common characters

ValueCountFrequency (%) 
.3504933.3%
 
03504933.3%
 
32314422.0%
 
167636.4%
 
251424.9%
 

Most frequent Latin characters

ValueCountFrequency (%) 
n1556866.7%
 
a778433.3%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII128499100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
.3504927.3%
 
03504927.3%
 
32314418.0%
 
n1556812.1%
 
a77846.1%
 
167635.3%
 
251424.0%
 

TITEL_KZ
Real number (ℝ≥0)

MISSING
SKEWED
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean0.009486979746
Minimum0
Maximum5
Zeros35698
Zeros (%)83.3%
Memory size334.8 KiB
2020-11-30T23:58:56.473455image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.1442365706
Coefficient of variation (CV)15.20363429
Kurtosis679.4086931
Mean0.009486979746
Median Absolute Deviation (MAD)0
Skewness23.54853598
Sum341
Variance0.0208041883
MonotocityNot monotonic
2020-11-30T23:58:56.577705image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
03569883.3%
 
12160.5%
 
415< 0.1%
 
510< 0.1%
 
35< 0.1%
 
(Missing)688916.1%
 
ValueCountFrequency (%) 
03569883.3%
 
12160.5%
 
35< 0.1%
 
415< 0.1%
 
510< 0.1%
 
ValueCountFrequency (%) 
510< 0.1%
 
415< 0.1%
 
35< 0.1%
 
12160.5%
 
03569883.3%
 

UMFELD_ALT
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7763
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean2.864756202
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:56.680149image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median3
Q34
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.304717603
Coefficient of variation (CV)0.4554375698
Kurtosis-1.09287365
Mean2.864756202
Median Absolute Deviation (MAD)1
Skewness0.04120127084
Sum100467
Variance1.702288023
MonotocityNot monotonic
2020-11-30T23:58:56.760835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
3930321.7%
 
4747617.5%
 
1712516.6%
 
2676715.8%
 
5439910.3%
 
(Missing)776318.1%
 
ValueCountFrequency (%) 
1712516.6%
 
2676715.8%
 
3930321.7%
 
4747617.5%
 
5439910.3%
 
ValueCountFrequency (%) 
5439910.3%
 
4747617.5%
 
3930321.7%
 
2676715.8%
 
1712516.6%
 

UMFELD_JUNG
Real number (ℝ≥0)

MISSING

Distinct5
Distinct (%)< 0.1%
Missing7763
Missing (%)18.1%
Infinite0
Infinite (%)0.0%
Mean4.254205874
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:56.849279image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q14
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.010633174
Coefficient of variation (CV)0.2375609466
Kurtosis1.412786321
Mean4.254205874
Median Absolute Deviation (MAD)0
Skewness-1.401782611
Sum149195
Variance1.021379413
MonotocityNot monotonic
2020-11-30T23:58:56.937352image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
51913344.7%
 
4915921.4%
 
3426510.0%
 
215863.7%
 
19272.2%
 
(Missing)776318.1%
 
ValueCountFrequency (%) 
19272.2%
 
215863.7%
 
3426510.0%
 
4915921.4%
 
51913344.7%
 
ValueCountFrequency (%) 
51913344.7%
 
4915921.4%
 
3426510.0%
 
215863.7%
 
19272.2%
 

UNGLEICHENN_FLAG
Boolean

MISSING

Distinct2
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Memory size334.8 KiB
0
33383 
1
 
2561
(Missing)
6889 
ValueCountFrequency (%) 
03338377.9%
 
125616.0%
 
(Missing)688916.1%
 

VERDICHTUNGSRAUM
Real number (ℝ≥0)

MISSING
ZEROS

Distinct46
Distinct (%)0.1%
Missing7784
Missing (%)18.2%
Infinite0
Infinite (%)0.0%
Mean4.43205227
Minimum0
Maximum45
Zeros17366
Zeros (%)40.5%
Memory size334.8 KiB
2020-11-30T23:58:57.060131image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile25
Maximum45
Range45
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.444763988
Coefficient of variation (CV)1.905384566
Kurtosis6.922586346
Mean4.43205227
Median Absolute Deviation (MAD)1
Skewness2.635257093
Sum155339
Variance71.31403882
MonotocityNot monotonic
2020-11-30T23:58:57.188835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%) 
01736640.5%
 
136848.6%
 
223885.6%
 
315703.7%
 
413683.2%
 
69402.2%
 
58832.1%
 
95351.2%
 
74951.2%
 
84811.1%
 
104271.0%
 
124081.0%
 
143940.9%
 
133210.7%
 
112800.7%
 
172470.6%
 
152440.6%
 
182440.6%
 
162260.5%
 
272000.5%
 
191550.4%
 
241540.4%
 
201420.3%
 
331270.3%
 
281180.3%
 
Other values (21)16523.9%
 
(Missing)778418.2%
 
ValueCountFrequency (%) 
01736640.5%
 
136848.6%
 
223885.6%
 
315703.7%
 
413683.2%
 
58832.1%
 
69402.2%
 
74951.2%
 
84811.1%
 
95351.2%
 
ValueCountFrequency (%) 
45650.2%
 
44670.2%
 
431040.2%
 
42400.1%
 
41280.1%
 
40420.1%
 
39690.2%
 
381070.2%
 
37520.1%
 
361030.2%
 

VERS_TYP
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size334.8 KiB
1
18486 
2
17015 
-1
7332 
ValueCountFrequency (%) 
11848643.2%
 
21701539.7%
 
-1733217.1%
 
2020-11-30T23:58:57.314600image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters3
Unique unicode categories2 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
12581851.5%
 
21701533.9%
 
-733214.6%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number4283385.4%
 
Dash Punctuation733214.6%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
12581860.3%
 
21701539.7%
 

Most frequent Dash Punctuation characters

ValueCountFrequency (%) 
-7332100.0%
 

Most occurring scripts

ValueCountFrequency (%) 
Common50165100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
12581851.5%
 
21701533.9%
 
-733214.6%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII50165100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
12581851.5%
 
21701533.9%
 
-733214.6%
 

VHA
Real number (ℝ≥0)

MISSING
ZEROS

Distinct6
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean1.132400401
Minimum0
Maximum5
Zeros16026
Zeros (%)37.4%
Memory size334.8 KiB
2020-11-30T23:58:57.401739image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.544135993
Coefficient of variation (CV)1.363595414
Kurtosis1.058262824
Mean1.132400401
Median Absolute Deviation (MAD)1
Skewness1.518056367
Sum40703
Variance2.384355966
MonotocityNot monotonic
2020-11-30T23:58:57.493263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
01602637.4%
 
11323930.9%
 
529606.9%
 
417744.1%
 
316783.9%
 
22670.6%
 
(Missing)688916.1%
 
ValueCountFrequency (%) 
01602637.4%
 
11323930.9%
 
22670.6%
 
316783.9%
 
417744.1%
 
529606.9%
 
ValueCountFrequency (%) 
529606.9%
 
417744.1%
 
316783.9%
 
22670.6%
 
11323930.9%
 
01602637.4%
 

VHN
Real number (ℝ≥0)

MISSING
ZEROS

Distinct5
Distinct (%)< 0.1%
Missing8303
Missing (%)19.4%
Infinite0
Infinite (%)0.0%
Mean2.372400811
Minimum0
Maximum4
Zeros1539
Zeros (%)3.6%
Memory size334.8 KiB
2020-11-30T23:58:57.582286image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median2
Q33
95-th percentile4
Maximum4
Range4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.151531347
Coefficient of variation (CV)0.4853865086
Kurtosis-0.9165564957
Mean2.372400811
Median Absolute Deviation (MAD)1
Skewness-0.08973374478
Sum81919
Variance1.326024442
MonotocityNot monotonic
2020-11-30T23:58:57.671463image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
21086225.4%
 
3788818.4%
 
4743017.3%
 
1681115.9%
 
015393.6%
 
(Missing)830319.4%
 
ValueCountFrequency (%) 
015393.6%
 
1681115.9%
 
21086225.4%
 
3788818.4%
 
4743017.3%
 
ValueCountFrequency (%) 
4743017.3%
 
3788818.4%
 
21086225.4%
 
1681115.9%
 
015393.6%
 

VK_DHT4A
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)< 0.1%
Missing7175
Missing (%)16.8%
Infinite0
Infinite (%)0.0%
Mean4.308682484
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:57.767119image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q37
95-th percentile10
Maximum11
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.169149267
Coefficient of variation (CV)0.7355262959
Kurtosis-1.234672811
Mean4.308682484
Median Absolute Deviation (MAD)2
Skewness0.4641746885
Sum153639
Variance10.04350708
MonotocityNot monotonic
2020-11-30T23:58:57.854656image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
11093825.5%
 
2441010.3%
 
1030287.1%
 
729947.0%
 
628066.6%
 
326656.2%
 
923495.5%
 
421645.1%
 
821555.0%
 
521445.0%
 
115< 0.1%
 
(Missing)717516.8%
 
ValueCountFrequency (%) 
11093825.5%
 
2441010.3%
 
326656.2%
 
421645.1%
 
521445.0%
 
628066.6%
 
729947.0%
 
821555.0%
 
923495.5%
 
1030287.1%
 
ValueCountFrequency (%) 
115< 0.1%
 
1030287.1%
 
923495.5%
 
821555.0%
 
729947.0%
 
628066.6%
 
521445.0%
 
421645.1%
 
326656.2%
 
2441010.3%
 

VK_DISTANZ
Real number (ℝ≥0)

MISSING

Distinct13
Distinct (%)< 0.1%
Missing7175
Missing (%)16.8%
Infinite0
Infinite (%)0.0%
Mean4.488473835
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:57.937837image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q37
95-th percentile11
Maximum13
Range12
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.27482938
Coefficient of variation (CV)0.72960866
Kurtosis-0.502728541
Mean4.488473835
Median Absolute Deviation (MAD)3
Skewness0.7172391234
Sum160050
Variance10.72450747
MonotocityNot monotonic
2020-11-30T23:58:58.038071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%) 
1852419.9%
 
2553012.9%
 
640729.5%
 
334748.1%
 
430827.2%
 
730007.0%
 
819264.5%
 
914823.5%
 
512212.9%
 
1010832.5%
 
119742.3%
 
128812.1%
 
134091.0%
 
(Missing)717516.8%
 
ValueCountFrequency (%) 
1852419.9%
 
2553012.9%
 
334748.1%
 
430827.2%
 
512212.9%
 
640729.5%
 
730007.0%
 
819264.5%
 
914823.5%
 
1010832.5%
 
ValueCountFrequency (%) 
134091.0%
 
128812.1%
 
119742.3%
 
1010832.5%
 
914823.5%
 
819264.5%
 
730007.0%
 
640729.5%
 
512212.9%
 
430827.2%
 

VK_ZG11
Real number (ℝ≥0)

MISSING

Distinct11
Distinct (%)< 0.1%
Missing7175
Missing (%)16.8%
Infinite0
Infinite (%)0.0%
Mean3.090077963
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:58.132294image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile9
Maximum11
Range10
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.510134098
Coefficient of variation (CV)0.8123206365
Kurtosis1.070953554
Mean3.090077963
Median Absolute Deviation (MAD)1
Skewness1.351096642
Sum110186
Variance6.300773189
MonotocityNot monotonic
2020-11-30T23:58:58.221544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%) 
11339631.3%
 
2576413.5%
 
3515712.0%
 
435828.4%
 
521905.1%
 
614503.4%
 
910032.3%
 
79662.3%
 
89072.1%
 
109052.1%
 
113380.8%
 
(Missing)717516.8%
 
ValueCountFrequency (%) 
11339631.3%
 
2576413.5%
 
3515712.0%
 
435828.4%
 
521905.1%
 
614503.4%
 
79662.3%
 
89072.1%
 
910032.3%
 
109052.1%
 
ValueCountFrequency (%) 
113380.8%
 
109052.1%
 
910032.3%
 
89072.1%
 
79662.3%
 
614503.4%
 
521905.1%
 
435828.4%
 
3515712.0%
 
2576413.5%
 

W_KEIT_KIND_HH
Real number (ℝ≥0)

MISSING
ZEROS

Distinct7
Distinct (%)< 0.1%
Missing9619
Missing (%)22.5%
Infinite0
Infinite (%)0.0%
Mean4.489281628
Minimum0
Maximum6
Zeros711
Zeros (%)1.7%
Memory size334.8 KiB
2020-11-30T23:58:58.307871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median6
Q36
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.886903173
Coefficient of variation (CV)0.420312943
Kurtosis-0.8660117125
Mean4.489281628
Median Absolute Deviation (MAD)0
Skewness-0.78685764
Sum149107
Variance3.560403585
MonotocityNot monotonic
2020-11-30T23:58:58.392589image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
61810042.3%
 
2472111.0%
 
434598.1%
 
326136.1%
 
121655.1%
 
514453.4%
 
07111.7%
 
(Missing)961922.5%
 
ValueCountFrequency (%) 
07111.7%
 
121655.1%
 
2472111.0%
 
326136.1%
 
434598.1%
 
514453.4%
 
61810042.3%
 
ValueCountFrequency (%) 
61810042.3%
 
514453.4%
 
434598.1%
 
326136.1%
 
2472111.0%
 
121655.1%
 
07111.7%
 

WOHNDAUER_2008
Real number (ℝ≥0)

MISSING

Distinct9
Distinct (%)< 0.1%
Missing6889
Missing (%)16.1%
Infinite0
Infinite (%)0.0%
Mean8.727437124
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:58.481950image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q19
median9
Q39
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.013701608
Coefficient of variation (CV)0.1161511213
Kurtosis18.92412763
Mean8.727437124
Median Absolute Deviation (MAD)0
Skewness-4.317782501
Sum313699
Variance1.02759095
MonotocityNot monotonic
2020-11-30T23:58:58.569227image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%) 
93242175.7%
 
814723.4%
 
44811.1%
 
64491.0%
 
73740.9%
 
53610.8%
 
33480.8%
 
1270.1%
 
211< 0.1%
 
(Missing)688916.1%
 
ValueCountFrequency (%) 
1270.1%
 
211< 0.1%
 
33480.8%
 
44811.1%
 
53610.8%
 
64491.0%
 
73740.9%
 
814723.4%
 
93242175.7%
 
ValueCountFrequency (%) 
93242175.7%
 
814723.4%
 
73740.9%
 
64491.0%
 
53610.8%
 
44811.1%
 
33480.8%
 
211< 0.1%
 
1270.1%
 

WOHNLAGE
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing7627
Missing (%)17.8%
Infinite0
Infinite (%)0.0%
Mean4.088280407
Minimum0
Maximum8
Zeros122
Zeros (%)0.3%
Memory size334.8 KiB
2020-11-30T23:58:58.665402image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q13
median3
Q37
95-th percentile7
Maximum8
Range8
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.05397709
Coefficient of variation (CV)0.5024061184
Kurtosis-1.161341184
Mean4.088280407
Median Absolute Deviation (MAD)1
Skewness0.4003864435
Sum143932
Variance4.218821886
MonotocityNot monotonic
2020-11-30T23:58:58.752971image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%) 
31126226.3%
 
7934121.8%
 
2495411.6%
 
4456210.7%
 
124235.7%
 
520524.8%
 
84901.1%
 
01220.3%
 
(Missing)762717.8%
 
ValueCountFrequency (%) 
01220.3%
 
124235.7%
 
2495411.6%
 
31126226.3%
 
4456210.7%
 
520524.8%
 
7934121.8%
 
84901.1%
 
ValueCountFrequency (%) 
84901.1%
 
7934121.8%
 
520524.8%
 
4456210.7%
 
31126226.3%
 
2495411.6%
 
124235.7%
 
01220.3%
 

ZABEOTYP
Real number (ℝ≥0)

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.800037354
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:58.842600image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median3
Q33
95-th percentile4
Maximum6
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.120623725
Coefficient of variation (CV)0.4002174197
Kurtosis1.132904877
Mean2.800037354
Median Absolute Deviation (MAD)0
Skewness0.254081768
Sum119934
Variance1.255797533
MonotocityNot monotonic
2020-11-30T23:58:58.929288image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%) 
32675362.5%
 
1840919.6%
 
441999.8%
 
616673.9%
 
215193.5%
 
52860.7%
 
ValueCountFrequency (%) 
1840919.6%
 
215193.5%
 
32675362.5%
 
441999.8%
 
52860.7%
 
616673.9%
 
ValueCountFrequency (%) 
616673.9%
 
52860.7%
 
441999.8%
 
32675362.5%
 
215193.5%
 
1840919.6%
 

ANREDE_KZ
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size334.8 KiB
2
25506 
1
17327 
ValueCountFrequency (%) 
22550659.5%
 
11732740.5%
 
2020-11-30T23:58:59.033981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%

Overview of Unicode Properties

Unique unicode characters2
Unique unicode categories1 ?
Unique unicode scripts1 ?
Unique unicode blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Most occurring characters

ValueCountFrequency (%) 
22550659.5%
 
11732740.5%
 

Most occurring categories

ValueCountFrequency (%) 
Decimal Number42833100.0%
 

Most frequent Decimal Number characters

ValueCountFrequency (%) 
22550659.5%
 
11732740.5%
 

Most occurring scripts

ValueCountFrequency (%) 
Common42833100.0%
 

Most frequent Common characters

ValueCountFrequency (%) 
22550659.5%
 
11732740.5%
 

Most occurring blocks

ValueCountFrequency (%) 
ASCII42833100.0%
 

Most frequent ASCII characters

ValueCountFrequency (%) 
22550659.5%
 
11732740.5%
 

ALTERSKATEGORIE_GROB
Real number (ℝ≥0)

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.220484206
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Memory size334.8 KiB
2020-11-30T23:58:59.127088image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q34
95-th percentile4
Maximum9
Range8
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.069753304
Coefficient of variation (CV)0.3321715729
Kurtosis1.68968059
Mean3.220484206
Median Absolute Deviation (MAD)0
Skewness-0.6295106719
Sum137943
Variance1.144372132
MonotocityNot monotonic
2020-11-30T23:58:59.212135image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
42274053.1%
 
31136026.5%
 
1530512.4%
 
233227.8%
 
91060.2%
 
ValueCountFrequency (%) 
1530512.4%
 
233227.8%
 
31136026.5%
 
42274053.1%
 
91060.2%
 
ValueCountFrequency (%) 
91060.2%
 
42274053.1%
 
31136026.5%
 
233227.8%
 
1530512.4%